subject:(Motion AND Path planning)

University of Alberta

1. Lei, Zhen. A robotic approach to the analysis of obstacle avoidance in crane lift path planning.

Degree: MS, Department of Civil and Environmental Engineering, 2011, University of Alberta

URL: https://era.library.ualberta.ca/files/tq57nr67z

► Crane lift path planning is time-consuming, prone to errors, and requires the practitioners to have exceptional visualization abilities, in particular, as the construction site is… (more)

Subjects/Keywords: Crane Lift; Path Planning; Motion Planning; Robotics

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APA (6^th Edition):

Lei, Z. (2011). A robotic approach to the analysis of obstacle avoidance in crane lift path planning. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/tq57nr67z

Chicago Manual of Style (16^th Edition):

Lei, Zhen. “A robotic approach to the analysis of obstacle avoidance in crane lift path planning.” 2011. Masters Thesis, University of Alberta. Accessed April 14, 2021. https://era.library.ualberta.ca/files/tq57nr67z.

MLA Handbook (7^th Edition):

Lei, Zhen. “A robotic approach to the analysis of obstacle avoidance in crane lift path planning.” 2011. Web. 14 Apr 2021.

Vancouver:

Lei Z. A robotic approach to the analysis of obstacle avoidance in crane lift path planning. [Internet] [Masters thesis]. University of Alberta; 2011. [cited 2021 Apr 14]. Available from: https://era.library.ualberta.ca/files/tq57nr67z.

Council of Science Editors:

Lei Z. A robotic approach to the analysis of obstacle avoidance in crane lift path planning. [Masters Thesis]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/tq57nr67z

2. Krontiris, Athanasios. Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles.

Degree: 2011, University of Nevada – Reno

URL: http://hdl.handle.net/11714/3828

► The first contribution of this work corresponds to a computationally efficient geometric method for simulating formations of systems with non-holonomic motion constraints inspired by solutions… (more)

Subjects/Keywords: Collision Avoidance; Formations; Motion Planning; Navigation; Path Planning; Physics-based Motion

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APA (6^th Edition):

Krontiris, A. (2011). Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles. (Thesis). University of Nevada – Reno. Retrieved from http://hdl.handle.net/11714/3828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Krontiris, Athanasios. “Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles.” 2011. Thesis, University of Nevada – Reno. Accessed April 14, 2021. http://hdl.handle.net/11714/3828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Krontiris, Athanasios. “Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles.” 2011. Web. 14 Apr 2021.

Vancouver:

Krontiris A. Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles. [Internet] [Thesis]. University of Nevada – Reno; 2011. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/11714/3828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Krontiris A. Improving Controllers for Formations and Deconfliction among Non-holonomic Vehicles. [Thesis]. University of Nevada – Reno; 2011. Available from: http://hdl.handle.net/11714/3828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Carnegie Mellon University

3. Knepper, Ross A. On the Fundamental Relationships Among Path Planning Alternatives.

Degree: 2011, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/180

► Robotic motion planning aspires to match the ease and efficiency with which humans move through and interact with their environment. Yet state of the art… (more)

▼ Robotic motion planning aspires to match the ease and efficiency with which humans move through and interact with their environment. Yet state of the art robotic planners fall short of human abilities; they are slower in computation, and the results are often of lower quality. One stumbling block in traditional motion planning is that points and paths are often considered in isolation. Many planners fail to recognize that substantial shared information exists among path alternatives. Exploitation of the geometric and topological relationships among path alternatives can therefore lead to increased efficiency and competency. These benefits include: better-informed path sampling, dramatically faster collision checking, and a deeper understanding of the trade-offs in path selection. In path sampling, the principle of locality is introduced as a basis for constructing an adaptive, probabilistic, geometric model to influence the selection of paths for collision test. Recognizing that collision testing consumes a sizable majority of planning time and that only collision-free paths provide value in selecting a path to execute on the robot, this model provides a significant increase in efficiency by circumventing collision testing paths that can be predicted to collide with obstacles. In the area of collision testing, an equivalence relation termed local path equivalence, is employed to discover when the work of testing a path has been previously performed. The swept volumes of adjoining path alternatives frequently overlap, implying that a continuum of intermediate paths exists as well. By recognizing such neighboring paths with related shapes and outcomes, up to 90% of paths may be tested implicitly in experiments, bypassing the traditional, expensive collision test and delivering a net 300% boost in collision test performance. Local path equivalence may also be applied to the path selection problem in order to recognize higher-level navigation options and make smarter choices. This thesis presents theoretical and experimental results in each of these three areas, as well as inspiration on the connections to how humans reason about moving through spaces.

Subjects/Keywords: motion planning; hierarchical planning; path sets; equivalence relation; homotopy; real-time planning; motion primitives; Robotics

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APA (6^th Edition):

Knepper, R. A. (2011). On the Fundamental Relationships Among Path Planning Alternatives. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/180

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Knepper, Ross A. “On the Fundamental Relationships Among Path Planning Alternatives.” 2011. Thesis, Carnegie Mellon University. Accessed April 14, 2021. http://repository.cmu.edu/dissertations/180.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Knepper, Ross A. “On the Fundamental Relationships Among Path Planning Alternatives.” 2011. Web. 14 Apr 2021.

Vancouver:

Knepper RA. On the Fundamental Relationships Among Path Planning Alternatives. [Internet] [Thesis]. Carnegie Mellon University; 2011. [cited 2021 Apr 14]. Available from: http://repository.cmu.edu/dissertations/180.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Knepper RA. On the Fundamental Relationships Among Path Planning Alternatives. [Thesis]. Carnegie Mellon University; 2011. Available from: http://repository.cmu.edu/dissertations/180

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Colorado

4. Coleman, David Thornton, IV. Methods for Improving Motion Planning Using Experience.

Degree: PhD, 2017, University of Colorado

URL: https://scholar.colorado.edu/csci_gradetds/153

► This thesis introduces new approaches to improve robotic motion planning by learning from past experiences especially suited for high-dimensional c-space with many invariant constraints.… (more)

▼ This thesis introduces new approaches to improve robotic motion planning by learning from past experiences especially suited for high-dimensional c-space with many invariant constraints. This experience-based motion planning (EBMP) paradigm reduces query resolution time, improves the quality of paths, and results in more predictable motions than typical probabilistic methods. Most previous approaches to motion planning have discarded past solution results and planned from scratch new solutions for every problem. A robot that is in operation for years will never get any better at its routine tasks. This thesis is novel in its focus on efficiently recalling previous motions the robot has performed and generalizing them to arbitrary new solutions even in the midst of changing obstacle environments. Several key difficulties present themselves in the reuse of previous experiences: efficient storage given memory constraints, quick recall for new queries, verification given changing environments, and adaptation/repair. These challenges are largely addressed by the use of sparse roadmaps that provide theoretical guarantees for asymptotic-near optimality, and lazy collision checking which allows iterative search through a large roadmap of motions. Improved sparse roadmap data structures for experience storage are presented that are optimized for the L¹-norm metric and large c-spaces. The trade-offs of full preprocessing of an experience roadmap for invariant constraints is studied. These new approaches are applied to the high-dimensional problems of humanoid whole body manipulation, dual-arm shelf picking, and multi-modal underconstrained Cartesian planning. Experiments are implemented in the MoveIt! Motion Planning framework and takeaways from developing robot-agnostic motion planning software are presented. Experimental results show two orders of magnitude speedups for solving difficult motion planning problems. Advisors/Committee Members: Nikolaus Correll, Sriram Sankaranarayanan, Christoffer Heckman, Mark Moll, Gabe Sibley.

Subjects/Keywords: experience; learning; motion planning; path planning; prm; sparse graphs; Robotics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Coleman, David Thornton, I. (2017). Methods for Improving Motion Planning Using Experience. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/csci_gradetds/153

Chicago Manual of Style (16^th Edition):

Coleman, David Thornton, IV. “Methods for Improving Motion Planning Using Experience.” 2017. Doctoral Dissertation, University of Colorado. Accessed April 14, 2021. https://scholar.colorado.edu/csci_gradetds/153.

MLA Handbook (7^th Edition):

Coleman, David Thornton, IV. “Methods for Improving Motion Planning Using Experience.” 2017. Web. 14 Apr 2021.

Vancouver:

Coleman, David Thornton I. Methods for Improving Motion Planning Using Experience. [Internet] [Doctoral dissertation]. University of Colorado; 2017. [cited 2021 Apr 14]. Available from: https://scholar.colorado.edu/csci_gradetds/153.

Council of Science Editors:

Coleman, David Thornton I. Methods for Improving Motion Planning Using Experience. [Doctoral Dissertation]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/csci_gradetds/153

University of Plymouth

5. Singh, Yogang. Cooperative swarm optimisation of unmanned surface vehicles.

Degree: PhD, 2019, University of Plymouth

URL: http://hdl.handle.net/10026.1/13700

► With growing advances in technology and everyday dependence on oceans for resources, the role of unmanned surface vehicles (USVs) has increased many fold. Extensive operations… (more)

▼ With growing advances in technology and everyday dependence on oceans for resources, the role of unmanned surface vehicles (USVs) has increased many fold. Extensive operations of USVs having naval, civil and scientiﬁc applications are currently being undertaken in various complex marine environments and demands are being placed on them to increase their autonomy and adaptability. A key requirement for the autonomous operation of USVs is to possess a multi-vehicle framework where they can operate as a ﬂeet of vehicles in a practical marine environment with multiple advantages such as surveying of wider areas in less time. From the literature, it is evident that a huge number of studies has been conducted in the area of single USV path planning, guidance and control whilst very few studies have been conducted to understand the implications of the multi vehicle approaches to USVs. This present PhD thesis integrates the modules of eﬃcient optimal path planning, robust path following guidance and cooperative swarm aggregation approach towards development of a new hybrid framework for cooperative navigation of swarm of USVs to enable optimal and autonomous operation in a maritime environment. Initially, an eﬀective and novel optimal path planning approach based on the A* algorithm has been designed taking into account the constraint of a safety distance from the obstacles to avoid the collisions in scenarios of moving obstacles and sea surface currents. This approach is then integrated with a novel virtual target path following guidance module developed for USVs where the reference trajectory from the path planner is fed into the guidance system. The novelty of the current work relies on combining the above mentioned integrated path following guidance system with decentralised swarm aggregation behaviour by means of simple potential based attraction and repulsion functions to maintain the centroid of the swarm of USVs and thereby guiding the swarm of USVs onto a reference path. Finally, an optimal and hybrid framework for cooperative navigation and guidance of ﬂeet of USVs, implementable in practical maritime environments and eﬀective for practical applications at sea is presented.

Subjects/Keywords: 623.8; USV; Path Planning; Swarm; Multi USV Motion Planning

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APA (6^th Edition):

Singh, Y. (2019). Cooperative swarm optimisation of unmanned surface vehicles. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/13700

Chicago Manual of Style (16^th Edition):

Singh, Yogang. “Cooperative swarm optimisation of unmanned surface vehicles.” 2019. Doctoral Dissertation, University of Plymouth. Accessed April 14, 2021. http://hdl.handle.net/10026.1/13700.

MLA Handbook (7^th Edition):

Singh, Yogang. “Cooperative swarm optimisation of unmanned surface vehicles.” 2019. Web. 14 Apr 2021.

Vancouver:

Singh Y. Cooperative swarm optimisation of unmanned surface vehicles. [Internet] [Doctoral dissertation]. University of Plymouth; 2019. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/10026.1/13700.

Council of Science Editors:

Singh Y. Cooperative swarm optimisation of unmanned surface vehicles. [Doctoral Dissertation]. University of Plymouth; 2019. Available from: http://hdl.handle.net/10026.1/13700

University of California – Merced

6. Mahmudi, Mentar. Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture.

Degree: Electrical Engineering and Computer Science, 2013, University of California – Merced

URL: http://www.escholarship.org/uc/item/6n27t9h1

► Planning the motions of a virtual character with high quality and control is a difficult challenge. Striking a balance between these two competing properties makes… (more)

▼ Planning the motions of a virtual character with high quality and control is a difficult challenge. Striking a balance between these two competing properties makes the problem particularly complex. While data-driven approaches produce high quality results due to the inherent realism of human motion capture data, planning algorithms are able to solve general continuous problems with a high degree of control. This dissertation addresses this overall problem with new techniques that combine the two approaches.Three main contributions are proposed. First, a simple and efficient motion capture segmentation mechanism is proposed based on geometric features that introduces semantic information for organizing a motion capture database into a motion graph. The obtained feature-based motion graph has less nodes and increased connectivity, which leads to improved searches in speed and coverage when compared to the standard approach. In addition, feature-based motion graphs enable a novel inverse branch kinematic deformation technique to be executed efficiently, allowing solution branches to be deformed towards precise goals without degrading the quality of the results.Second, in order to address speed of computation, precomputed motion maps are introduced for the interactive search and synthesis of locomotion sequences from unstructured feature-based motion graphs. Unstructured graphs can be successfully handled by relying on multiple maps and a search mechanism with backtracking information, which eliminates the need of manually creating fully connected move graphs. Precomputed motion maps can simultaneously search and execute motions in environments with many obstacles at interactive rates.Finally, a multi-modal data-driven framework is proposed for task-oriented human-like motion planning, which combines data-driven methods with parameterized motion skills in order to achieve human motions that are realistic and that have a high degree of controllability. The multi-modal planner relies on feature-based motion graphs for achieving a high-quality locomotion skill and integrates generic, task-specific data-based or algorithmic motion primitive skills for precise upper-body manipulation and action planning. The approach includes a multi-modal search method where primitive motion skills compete for contributing to the final solution.As a result, the overall proposed framework provides a high degree of control and, at the same time, retains the realism and human-likeness of motion capture data. Several examples are presented for synthesizing complex motions such as walking through doors, relocating books on shelves, etc.

Subjects/Keywords: Computer science; Robotics; Character Animation; Computer Animation; Motion Capture; Motion Planning; Path Planning

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APA (6^th Edition):

Mahmudi, M. (2013). Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/6n27t9h1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mahmudi, Mentar. “Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture.” 2013. Thesis, University of California – Merced. Accessed April 14, 2021. http://www.escholarship.org/uc/item/6n27t9h1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mahmudi, Mentar. “Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture.” 2013. Web. 14 Apr 2021.

Vancouver:

Mahmudi M. Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture. [Internet] [Thesis]. University of California – Merced; 2013. [cited 2021 Apr 14]. Available from: http://www.escholarship.org/uc/item/6n27t9h1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mahmudi M. Multi-Modal Planning for Humanlike Motion Synthesis using Motion Capture. [Thesis]. University of California – Merced; 2013. Available from: http://www.escholarship.org/uc/item/6n27t9h1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

7. Kim, Young Ho. Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning.

Degree: PhD, Computer Engineering, 2017, Texas A&M University

URL: http://hdl.handle.net/1969.1/161540

► Ropes and rope-like objects (e.g., chains, cords, lines, whips, or lassos) are comparatively cheap, simple, and useful in daily life. For a long time, humans… (more)

▼ Ropes and rope-like objects (e.g., chains, cords, lines, whips, or lassos) are comparatively cheap, simple, and useful in daily life. For a long time, humans have used such structures for manipulation tasks in a qualitatively different ways such as pulling, fastening, attaching, tying, knotting, and whipping. Nevertheless, these structures have received little attention in robotics. Because they are unactuated, such structures are regarded as difficult to model, plan and control. In this dissertation, we are interested in a mobile robot system using a flexible rope-like structure attached to its end akin to a ‘tail’. Our goal is to investigate how mobile robots can use compliant, unactuated structures for various manipulation tasks. Robots that use a tail to manipulate objects face challenges in modeling and planning of behaviors, dynamics, and combinatorial optimization. In this dissertation, we propose several methods to deal with the difficulties of modeling and planning. In addition, we solve variants of object manipulation problems wherein multiple classes of objects are to be transported by multiple cooperative robots using ropes. Firstly, we examine motion primitives, where the primitives are designed to simplify modeling and planning issues. We explore several sets of motion primitive where each primitive contributes some aspect lacking in the others. These primitives are forward models of the system’s behavior that predict the position and orientation of the object being manipulated within the workspace. Then, to solve manipulation problems, we design a planner that seeks a sequence of motion primitives by using a sampling-based motion planning approach coupled with a particle-based representation to treat error propagation of the motions. Our proposed planner is used to optimize motion sequences based on a specified preference over a set of objectives, such as execution time, navigation cost, or collision likelihood. The solutions deal with different preferences effectively, and we analyze the complementary nature of dynamic and quasi-static motions, showing that there exist regimes where transitions among them are indeed desirable, as reflected in the plans produced. Secondly, we explore a variety of interesting primitives that result in new approaches for object manipulation problems. We examine ways two robots can join the ends of their tails so that a pair of conjoined robots can encircle objects leading to the advantage of greater towing capacity if they work cooperatively. However, individual robots possess the advantage of allowing for greater concurrency if objects are distant from one another. We solve a new manipulation problem for the scenarios of moving a collection of objects to goal locations with multiple robots that may form conjoined pairs. To maximize efficiency, the robots balance working as a tightly-knit sub-team with individual operation. We develop heuristics that give satisfactory solutions in reasonable time. The results we report include data from physical robots executing… Advisors/Committee Members: Shell, Dylan A (advisor), Akleman, Ergun (committee member), Gutierrez-Osuna, Ricardo (committee member), Song, Dezhen (committee member).

Subjects/Keywords: Manipulation Planning; Motion and Path planning; Underactuated Robots; Flexible Robots; Multi-robot Task Planning; Multi-robot Path Planning; Cooperative Robot Teams

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kim, Y. H. (2017). Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161540

Chicago Manual of Style (16^th Edition):

Kim, Young Ho. “Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning.” 2017. Doctoral Dissertation, Texas A&M University. Accessed April 14, 2021. http://hdl.handle.net/1969.1/161540.

MLA Handbook (7^th Edition):

Kim, Young Ho. “Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning.” 2017. Web. 14 Apr 2021.

Vancouver:

Kim YH. Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1969.1/161540.

Council of Science Editors:

Kim YH. Manipulating Objects using Compliant, Unactuated Tails: Modeling and Planning. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161540

University of Pennsylvania

8. Cohen, Benjamin. Motion Planning for Manipulation With Heuristic Search.

Degree: 2015, University of Pennsylvania

URL: https://repository.upenn.edu/edissertations/1663

► Heuristic searches such as A* search are a popular means of finding least-cost plans due to their generality, strong theoretical guarantees on completeness and optimality,… (more)

▼ Heuristic searches such as A* search are a popular means of finding least-cost plans due to their generality, strong theoretical guarantees on completeness and optimality, simplicity in implementation, and consistent behavior. In planning for robotic manipulation, however, these techniques are commonly thought of as impractical due to the high-dimensionality of the planning problem. As part of this thesis work, we have developed a heuristic search-based approach to motion planning for manipulation that does deal effectively with the high-dimensionality of the problem. In this thesis, I will present the approach together with its theoretical properties and show how to apply it to single-arm and dual-arm motion planning with upright constraints on a PR2 robot operating in non-trivial cluttered spaces. Then I will explain how we extended our approach to manipulation planning for n-arms with regrasping. In this work, the planner itself makes all of the discrete decisions, including which arm to use for the pickup and putdown, whether handoffs are necessary and how the object should be grasped at each step along the way. An extensive experimental analysis in both simulation and on a physical PR2 shows that, in terms of runtime, our approach is on par with some of the most common sampling-based approaches. This includes benchmarking our planning framework on two domains that we constructed that are common to manufacturing: pick-and-place of fast moving objects and the autonomous assembly of small objects. Between these applications, the planner exhibited fast planning times and the ability to robustly plan paths into and out of tight working environments that are common to assembly. The closing work of this thesis includes an exhaustive study of the natural tradeoff that occurs between planning efficiency versus solution quality for different values of the heuristic inflation factor. A comparison of the solution quality of our planner to paths computed by an asymptotically optimal approach given a great deal of time for path optimization is included as well. Finally, a set of experimental results are included that show that due to our approach's deterministic cost-minimization, similar input tends to lead to similarity in the output. This kind of local consistency is important to the predictability of the robot's motions and contributes to human-robot safety.

Subjects/Keywords: heuristic search; manipulation; motion planning; path planning; robot arm; search-based planning; Computer Sciences; Robotics

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APA (6^th Edition):

Cohen, B. (2015). Motion Planning for Manipulation With Heuristic Search. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/1663

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cohen, Benjamin. “Motion Planning for Manipulation With Heuristic Search.” 2015. Thesis, University of Pennsylvania. Accessed April 14, 2021. https://repository.upenn.edu/edissertations/1663.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cohen, Benjamin. “Motion Planning for Manipulation With Heuristic Search.” 2015. Web. 14 Apr 2021.

Vancouver:

Cohen B. Motion Planning for Manipulation With Heuristic Search. [Internet] [Thesis]. University of Pennsylvania; 2015. [cited 2021 Apr 14]. Available from: https://repository.upenn.edu/edissertations/1663.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cohen B. Motion Planning for Manipulation With Heuristic Search. [Thesis]. University of Pennsylvania; 2015. Available from: https://repository.upenn.edu/edissertations/1663

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

9. Haak, Kasper (author). Lyapunov Stable Path Planning and Control for Autonomous Vehicles.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:b65216fa-483f-4b0f-8e22-ba188010f696

►

In modern society cars are one of the most important means of transportation. Unfortunately, many people die in car accidents around the world. Research shows… (more)

▼

In modern society cars are one of the most important means of transportation. Unfortunately, many people die in car accidents around the world. Research shows that the number of fatal casualties in car accidents has been increasing for the past decade and that the largest cause of these accidents is the human driver. For this reason, research on fully autonomous vehicles has gained a lot of attention. However, currently autonomous driving is only implemented to reduce the errors of human drivers. More research is necessary in order for fully autonomous vehicles to be implemented and to remove the human driver completely. A robust navigation algorithm which is able to run in real time is one of the challenges in development of fully autonomous vehicles. Important topics in navigation of autonomous vehicles include the path planner and the motion controller. The path planner ﬁnds a path for the vehicle from its current location to the target location. At the same time the path planner avoids obstacles and fulﬁlls the non-holonomic constraints of the autonomous vehicle. The motion controller tries to follow the path the path planner made as close as possible by controlling the vehicle. These two topics inﬂuence each other and are therefore dependent. In literature little research is done on integrated algorithms that combine path planning and motion control. Therefore, this thesis will research navigation of autonomous vehicles by using an integrated algorithm that includes both path planning and motion control. The objective of this thesis is to develop a Lyapunov stable control algorithm that is capable of planning a path for all possible vehicle maneuvers. Besides path planning the proposed algorithm must be capable of controlling the vehicle along this path. Furthermore, the algorithm needs to include obstacles and the non-holonomic dynamics of an autonomous vehicle. The main contribution of this thesis is an integrated path planner and motion controller for navigation of autonomous vehicles. The stability of the proposed algorithm is proven by using the Lyapunov method. Simulation results prove that the algorithm is capable of planning the path and the motion of the autonomous vehicle with non-holonomic constraints and with the presence of obstacles.

Mechanical Engineering | Systems and Control

Advisors/Committee Members: Alirezaei, Mohsen (mentor), Hellendoorn, Hans (graduation committee), Batselier, Kim (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Lyapunov Stability; Autonomous Vehicles; Path Planning; Motion Control

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APA (6^th Edition):

Haak, K. (. (2019). Lyapunov Stable Path Planning and Control for Autonomous Vehicles. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b65216fa-483f-4b0f-8e22-ba188010f696

Chicago Manual of Style (16^th Edition):

Haak, Kasper (author). “Lyapunov Stable Path Planning and Control for Autonomous Vehicles.” 2019. Masters Thesis, Delft University of Technology. Accessed April 14, 2021. http://resolver.tudelft.nl/uuid:b65216fa-483f-4b0f-8e22-ba188010f696.

MLA Handbook (7^th Edition):

Haak, Kasper (author). “Lyapunov Stable Path Planning and Control for Autonomous Vehicles.” 2019. Web. 14 Apr 2021.

Vancouver:

Haak K(. Lyapunov Stable Path Planning and Control for Autonomous Vehicles. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 14]. Available from: http://resolver.tudelft.nl/uuid:b65216fa-483f-4b0f-8e22-ba188010f696.

Council of Science Editors:

Haak K(. Lyapunov Stable Path Planning and Control for Autonomous Vehicles. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:b65216fa-483f-4b0f-8e22-ba188010f696

Virginia Tech

10. Grymin, David J. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles .

Degree: PhD, Aerospace Engineering, 2013, Virginia Tech

URL: http://hdl.handle.net/10919/24520

► This dissertation addresses motion planning, modeling, and feedback control for autonomous vehicle systems. A hierarchical approach for motion planning and control of nonlinear systems operating… (more)

▼ This dissertation addresses motion planning, modeling, and feedback control for autonomous vehicle systems. A hierarchical approach for motion planning and control of nonlinear systems operating in obstacle environments is presented. To reduce computation time during the motion planning process, dynamically feasible trajectories are generated in real-time through concatenation of pre-specified motion primitives. The motion planning task is posed as a search over a directed graph, and the applicability of informed graph search techniques is investigated. Specifically, a locally greedy algorithm with effective backtracking ability is developed and compared to weighted A* search. The greedy algorithm shows an advantage with respect to solution cost and computation time when larger motion primitive libraries that do not operate on a regular state lattice are utilized. Linearization of the nonlinear system equations about the motion primitive library results in a hybrid linear time-varying model, and an optimal control algorithm using the L2-induced norm as the performance measure is applied to ensure that the system tracks the desired trajectory. The ability of the resulting controller to closely track the trajectory obtained from the motion planner, despite various disturbances and uncertainties, is demonstrated through simulation. Additionally, an approach for obtaining dynamically feasible reference trajectories and feedback controllers for a small unmanned aerial vehicle (UAV) based on an aerodynamic model derived from flight tests is presented. The modeling approach utilizes the two step method (TSM) with stepwise multiple regression to determine relevant explanatory terms for the aerodynamic models. Dynamically feasible trajectories are then obtained through the solution of an optimal control problem using pseudospectral optimal control software. Discrete-time feedback controllers are then obtained to regulate the vehicle along the desired reference trajectory. Simulations in a realistic operational environment as well as flight testing with the feedback controller demonstrate the capabilities of the approach. The TSM is also applied for system identification of an aircraft using motion capture data. In this application, time domain system identification techniques are used to identify both linear and nonlinear aerodynamic models of large-amplitude pitching motions driven by control surface deflections. The resulting models are assessed based on both their predictive capabilities as well as simulation results. Advisors/Committee Members: Farhood, Mazen H. (committeechair), Woolsey, Craig A. (committee member), Sultan, Cornel (committee member), Patil, Mayuresh J. (committee member).

Subjects/Keywords: Aircraft; Motion Primitives; Parameter Estimation; Path Planning; System Identification; Trajectory Generation

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APA (6^th Edition):

Grymin, D. J. (2013). Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles . (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/24520

Chicago Manual of Style (16^th Edition):

Grymin, David J. “Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles .” 2013. Doctoral Dissertation, Virginia Tech. Accessed April 14, 2021. http://hdl.handle.net/10919/24520.

MLA Handbook (7^th Edition):

Grymin, David J. “Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles .” 2013. Web. 14 Apr 2021.

Vancouver:

Grymin DJ. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles . [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/10919/24520.

Council of Science Editors:

Grymin DJ. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles . [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/24520

Universiteit Utrecht

11. Berg, J.P. van den. Path planning in dynamic environments.

Degree: 2007, Universiteit Utrecht

URL: http://dspace.library.uu.nl:8080/handle/1874/20873

► Path planning plays an important role in various fields of application, such as CAD design, computer games and virtual environments, molecular biology, and robotics. In… (more)

Subjects/Keywords: Wiskunde en Informatica; robotics; computational geometry; path planning; motion planning; dynamic environments

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APA (6^th Edition):

Berg, J. P. v. d. (2007). Path planning in dynamic environments. (Doctoral Dissertation). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/20873

Chicago Manual of Style (16^th Edition):

Berg, J P van den. “Path planning in dynamic environments.” 2007. Doctoral Dissertation, Universiteit Utrecht. Accessed April 14, 2021. http://dspace.library.uu.nl:8080/handle/1874/20873.

MLA Handbook (7^th Edition):

Berg, J P van den. “Path planning in dynamic environments.” 2007. Web. 14 Apr 2021.

Vancouver:

Berg JPvd. Path planning in dynamic environments. [Internet] [Doctoral dissertation]. Universiteit Utrecht; 2007. [cited 2021 Apr 14]. Available from: http://dspace.library.uu.nl:8080/handle/1874/20873.

Council of Science Editors:

Berg JPvd. Path planning in dynamic environments. [Doctoral Dissertation]. Universiteit Utrecht; 2007. Available from: http://dspace.library.uu.nl:8080/handle/1874/20873

Penn State University

12. Nedorezov, Adam Jonathan. Active Contour Motion Planning in the Inverse Perspective Mapping Frame.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/13364ajn5049

► This work explores the use of active contours for the purposes of motion planning in a highway environment. Traditionally active contours have been used in… (more)

Subjects/Keywords: Active Contour; Path Planning; Vanishing Point Estimation; Inverse Perspective Mapping; Motion Planning; Obstacle Detection

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APA (6^th Edition):

Nedorezov, A. J. (2016). Active Contour Motion Planning in the Inverse Perspective Mapping Frame. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13364ajn5049

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nedorezov, Adam Jonathan. “Active Contour Motion Planning in the Inverse Perspective Mapping Frame.” 2016. Thesis, Penn State University. Accessed April 14, 2021. https://submit-etda.libraries.psu.edu/catalog/13364ajn5049.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nedorezov, Adam Jonathan. “Active Contour Motion Planning in the Inverse Perspective Mapping Frame.” 2016. Web. 14 Apr 2021.

Vancouver:

Nedorezov AJ. Active Contour Motion Planning in the Inverse Perspective Mapping Frame. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Apr 14]. Available from: https://submit-etda.libraries.psu.edu/catalog/13364ajn5049.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nedorezov AJ. Active Contour Motion Planning in the Inverse Perspective Mapping Frame. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/13364ajn5049

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Duke University

13. Lu, Wenjie. Autonomous Sensor Path Planning and Control for Active Information Gathering .

Degree: 2014, Duke University

URL: http://hdl.handle.net/10161/9409

► Sensor path planning and control refer to the problems of determining the trajectory and feedback control law that best support sensing objectives, such as… (more)

▼ Sensor path planning and control refer to the problems of determining the trajectory and feedback control law that best support sensing objectives, such as monitoring, detection, classification, and tracking. Many autonomous systems developed, for example, to conduct environmental monitoring, search-and-rescue operations, demining, or surveillance, consist of a mobile vehicle instrumented with a suite of proprioceptive and exteroceptive sensors characterized by a bounded field-of-view (FOV) and a performance that is highly dependent on target and environmental conditions and, thus, on the vehicle position and orientation relative to the target and the environment. As a result, the sensor performance can be significantly improved by planning the vehicle motion and attitude in concert with the measurement sequence. This dissertation develops a general and systematic approach for deriving information-driven path planning and control methods that maximize the expected utility of the sensor measurements subject to the vehicle kinodynamic constraints. The approach is used to develop three path planning and control methods: the information potential method (IP) for integrated path planning and control, the optimized coverage planning based on the Dirichlet process-Gaussian process (DP-GP) expected Kullback-Leibler (KL) divergence, and the optimized visibility planning for simultaneous target tracking and localization. The IP method is demonstrated on a benchmark problem, referred to as treasure hunt, in which an active vision sensor is mounted on a mobile unicycle platform and is deployed to classify stationary targets characterized by discrete random variables, in an obstacle-populated environment. In the IP method, an artificial potential function is generated from the expected conditional mutual information of the targets and is used to design a closed-loop switched controller. The information potential is also used to construct an information roadmap for escaping local minima. Theoretical analysis shows that the closed-loop robotic system is asymptotically stable and that an escaping path can be found when the robotic sensor is trapped in a local minimum. Numerical simulation results show that this method outperforms rapidly-exploring random trees and classical potential methods. The optimized coverage planning method maximizes the DP-GP expected KL divergence approximated by Monte Carlo integration in order to optimize the information value of a vision sensor deployed to track and model multiple moving targets. The variance of the KL approximation error is proven to decrease linearly with the inverse of the number of samples. This approach is demonstrated through a camera-intruder problem, in which the camera pan, tilt, and zoom variables are controlled to model multiple moving targets with unknown kinematics by nonparametric DP-GP mixture models. Numerical simulations as well as physical experiments show that the optimized coverage planning approach outperforms other applicable algorithms, such as methods… Advisors/Committee Members: Ferrari, Silvia (advisor).

Subjects/Keywords: Mechanical engineering; Computer engineering; Adaptive Control; Information; Motion Planning; Path Planning; Sensor Control; Switched Systems

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APA (6^th Edition):

Lu, W. (2014). Autonomous Sensor Path Planning and Control for Active Information Gathering . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/9409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lu, Wenjie. “Autonomous Sensor Path Planning and Control for Active Information Gathering .” 2014. Thesis, Duke University. Accessed April 14, 2021. http://hdl.handle.net/10161/9409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lu, Wenjie. “Autonomous Sensor Path Planning and Control for Active Information Gathering .” 2014. Web. 14 Apr 2021.

Vancouver:

Lu W. Autonomous Sensor Path Planning and Control for Active Information Gathering . [Internet] [Thesis]. Duke University; 2014. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/10161/9409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lu W. Autonomous Sensor Path Planning and Control for Active Information Gathering . [Thesis]. Duke University; 2014. Available from: http://hdl.handle.net/10161/9409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

14. Wallace, Nathan Daniel. Energy-aware Planning and Control of Off-road Wheeled Mobile Robots .

Degree: 2020, University of Sydney

URL: http://hdl.handle.net/2123/23221

► In modern agriculture, many of the tasks necessary for the smooth operation of a farm can be categorised as dull, dirty, or dangerous. This makes… (more)

▼ In modern agriculture, many of the tasks necessary for the smooth operation of a farm can be categorised as dull, dirty, or dangerous. This makes such operations a prime candidate for automation. However, most agricultural properties are vast, often encompassing large areas of undulating off-road terrain with varying traction conditions, making them difficult to traverse for wheeled platforms. Furthermore, the large scale of these properties necessitates careful consideration and management of resources – especially energy or fuel – in the planning of missions, to traverse these large distances and successfully achieve objectives without the risk of stranding the platform out in the field. These challenges need to be addressed before autonomous wheeled mobile robots are ready for deployment in agricultural contexts. This thesis seeks to address some of the key issues that impact the feasibility of deploying wheeled mobile robots in the field, focusing on off-road mobility and the generation of energy-efficient plans for these platforms. In the case of agricultural applications, where the robot may be required to operate near crops and livestock, accurate navigation is of utmost importance, and achieving this in the presence of difficult off-road conditions is a major challenge. The solution proposed in this work is an optimisation-based estimation and control strategy for accurate trajectory tracking in the presence of slip. A novel structured parameter blocking extension to this strategy is developed and tested, and shown to improve state estimation and path tracking performance for traversal over rapidly varying terrain conditions. To address the problem of efficiency, a data-driven energy cost of motion model for an omnidirectional wheeled mobile robot is then developed, and asymptotically optimal sampling-based planners exploiting this model, along with consideration of various terrain features and the configuration of the platform itself, are presented.

Subjects/Keywords: field robotics; estimation; mobile robots; motion control; path planning; energy-efficient planning

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APA (6^th Edition):

Wallace, N. D. (2020). Energy-aware Planning and Control of Off-road Wheeled Mobile Robots . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/23221

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wallace, Nathan Daniel. “Energy-aware Planning and Control of Off-road Wheeled Mobile Robots .” 2020. Thesis, University of Sydney. Accessed April 14, 2021. http://hdl.handle.net/2123/23221.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wallace, Nathan Daniel. “Energy-aware Planning and Control of Off-road Wheeled Mobile Robots .” 2020. Web. 14 Apr 2021.

Vancouver:

Wallace ND. Energy-aware Planning and Control of Off-road Wheeled Mobile Robots . [Internet] [Thesis]. University of Sydney; 2020. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/2123/23221.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wallace ND. Energy-aware Planning and Control of Off-road Wheeled Mobile Robots . [Thesis]. University of Sydney; 2020. Available from: http://hdl.handle.net/2123/23221

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Guelph

15. Shahriari, Mohammadali. Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots.

Degree: PhD, School of Engineering, 2017, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/10456

► Navigation of multiple mobile robots (MMRs) has gained significant interest in recent years because of its growing applications such as in exploration, search and rescue,… (more)

▼ Navigation of multiple mobile robots (MMRs) has gained significant interest in recent years because of its growing applications such as in exploration, search and rescue, and scientific data collection. Many of these applications require collision-free navigation of MMRs to allow safe and efficient operation which is subjected to many challenges, such as dynamic and cluttered environments, robots' kinematic and dynamic constraints, motion-liveness, and scalability for large-scale systems. Therefore, this thesis develops navigation methodologies for two models of robots: (i) kinematics and (ii) dynamics; both in centralized and distributed schemes. For navigation of MMRs considering kinematics in the centralized scheme, a new conflict resolution strategy is developed that coordinates the robots using only velocity to ensure motion-liveness, especially for cluttered and dynamic environments. Results showed this method is scalable while satisfies robots' non-holonomic and velocity constraints. Regarding the distributed scheme, a new predictive collision avoidance methodology is developed that navigates the robots safely through environment uncertainties relying only on onboard sensors. A robust non-linear controller is subsequently designed to achieve simultaneous tracking and collision avoidance of the robots. For navigation of MMRs considering dynamics, one key element for their safe navigation is the calculation of the time to collision (TTC). A generic method is presented for calculating the TTC among MMRs based on their dynamics to effectively quantify the collision potential and subsequently develop new distributed and centralized navigation methodologies. The results verified that the developed methods are more reliable navigation especially for MMRs with different masses and provide a safer distance among them compared to kinematics-based methods, notably in confined spaces in which some conservative cases result in failures. It was shown in simulations and experiments that the consideration of robots' mass and dynamics are imperative for safety and energy efficiency of MMRs. This thesis enhanced the collision-free navigation methodologies for cluttered and dynamic environments with live and deadlock-free motion. The developed methodologies are scalable and tried to address the MMRs' collision-free navigation issues with realistic constraints. As a future work, more efficient algorithms can be developed to reduce the computational costs of the proposed navigation methodologies for MMRs. Advisors/Committee Members: Biglarbegian, Mohammad (advisor).

Subjects/Keywords: robotics; mobile robots; control; navigation; optimization; multi-robots; motion control; path planning; motion planning; collision avoidance; robots autonomy

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APA (6^th Edition):

Shahriari, M. (2017). Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots. (Doctoral Dissertation). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/10456

Chicago Manual of Style (16^th Edition):

Shahriari, Mohammadali. “Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots.” 2017. Doctoral Dissertation, University of Guelph. Accessed April 14, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/10456.

MLA Handbook (7^th Edition):

Shahriari, Mohammadali. “Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots.” 2017. Web. 14 Apr 2021.

Vancouver:

Shahriari M. Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots. [Internet] [Doctoral dissertation]. University of Guelph; 2017. [cited 2021 Apr 14]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/10456.

Council of Science Editors:

Shahriari M. Development of Collision-Free Navigation Methodologies for Multiple Mobile Robots. [Doctoral Dissertation]. University of Guelph; 2017. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/10456

Linköping University

16. Hellander, Anja. Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization.

Degree: Automatic Control, 2020, Linköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582

► Motion planning is defined as the problem of computing a feasible trajectory for an agent to follow. It is a well-studied problem with applications… (more)

▼ Motion planning is defined as the problem of computing a feasible trajectory for an agent to follow. It is a well-studied problem with applications in fields such as robotics, control theory and artificial intelligence. In the last decade there has been an increased interest in algorithms for motion planning under uncertainty where the agent does not know the state of the environment due to, e.g. motion and sensing uncertainties. One approach is to generate an initial feasible trajectory using for example an algorithm such as RRT* and then improve that initial trajectory using local optimization. This thesis proposes a new modification of the RRT* algorithm that can be used to generate initial paths from which initial trajectories for the local optimization step can be generated. Unlike standard RRT*, the modified RRT* generates multiple paths at the same time, all belonging to different families of solutions (homotopy classes). Algorithms for motion planning under uncertainty that rely on local optimization of trajectories can use trajectories generated from these paths as initial solutions. The modified RRT* is implemented and its performance with respect to computation time and number of paths found is evaluated on simple scenarios. The evaluations show that the modified RRT* successfully computes solutions in multiple homotopy classes. Two methods for motion planning under uncertainty, Trajectory-optimized LQG (T-LQG), and a belief space variant of iterative LQG (iLQG) are implemented and combined with the modified RRT*. The performance with respect to cost function improvement, computation time and success rate when following the optimized trajectories for the two methods are evaluated in a simulation study. The results from the simulation studies show that it is advantageous to generate multiple initial trajectories. Some initial trajectories, due to for example passing through narrow passages or through areas with high uncertainties, can only be slightly improved by trajectory optimization or results in trajectories that are hard to follow or with a high collision risk. If multiple initial trajectories are generated the probability is higher that at least one of them will result in an optimized trajectory that is easy to follow, with lower uncertainty and lower collision risk than the initial trajectory. The results also show that iLQG is much more computationally expensive than T-LQG, but that it is better at computing control policies to follow the optimized trajectories.

Subjects/Keywords: Motion planning; Path planning; Local optimization; RRT*; Homotopy; LQG; Belief space planning; Optimal control; Control Engineering; Reglerteknik

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APA (6^th Edition):

Hellander, A. (2020). Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hellander, Anja. “Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization.” 2020. Thesis, Linköping University. Accessed April 14, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hellander, Anja. “Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization.” 2020. Web. 14 Apr 2021.

Vancouver:

Hellander A. Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization. [Internet] [Thesis]. Linköping University; 2020. [cited 2021 Apr 14]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hellander A. Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization. [Thesis]. Linköping University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

17. Autere, Antti. Extensions and Applications of the A* Algorithm.

Degree: 2005, Helsinki University of Technology

URL: http://lib.tkk.fi/Diss/2005/isbn9512279487/

►

In this thesis we investigate path finding problems, that is, planning routes from a start node to some goal nodes in a graph. Such problems… (more)

▼

In this thesis we investigate path finding problems, that is, planning routes from a start node to some goal nodes in a graph. Such problems arise in many fields of technology, for example, production planning, energy-aware message routing in large networks, resource allocation, and vehicle navigation systems. We concentrate mostly on planning a minimum cost path using the A* algorithm. We begin by proving new theorems comparing the performance of A* to other (generalized) path finding algorithms. In some cases, A* is an optimal method in a large class of algorithms. This means, roughly speaking, that A* explores a smaller region of the search space than the other algorithms in the given class. We develop a new method of improving a given (static) heuristic for A* dynamically, during search. A heuristic controls the search of A* so that unnecessary branches of the tree of nodes that A* visits are pruned. The new method also finds an optimal path to any node it visits for the first time so that every node will be visited only once. The latter is an important property considering the efficiency of the search. We examine the use of A* as a higher level method to allocate resources among several path finding algorithms. In some cases, the A* is an optimal resource allocation method, which means that the number of the nodes the path finding algorithms together visit is minimized. As applications of A*, we have developed new hierarchical algorithms for robot point-to-point path planning tasks, and new algorithms for power-aware routing of messages in large communication networks. The new algorithms are more robust than some older ones to which we compare. Moreover, one of the message routing algorithms produces higher average lifetimes of the network than those of the widely quoted max-min zPmin algorithm.

Helsinki University of Technology, Laboratory for Theoretical Computer Science. A, Research reports, ISSN 1457-7615; 98

Advisors/Committee Members: Helsinki University of Technology, Department of Computer Science and Engineering, Laboratory for Theoretical Computer Science.

Subjects/Keywords: path finding; heuristic algorithms; best-first search; A*; resource allocation; robotics; motion planning; message routing

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APA (6^th Edition):

Autere, A. (2005). Extensions and Applications of the A* Algorithm. (Thesis). Helsinki University of Technology. Retrieved from http://lib.tkk.fi/Diss/2005/isbn9512279487/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Autere, Antti. “Extensions and Applications of the A* Algorithm.” 2005. Thesis, Helsinki University of Technology. Accessed April 14, 2021. http://lib.tkk.fi/Diss/2005/isbn9512279487/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Autere, Antti. “Extensions and Applications of the A* Algorithm.” 2005. Web. 14 Apr 2021.

Vancouver:

Autere A. Extensions and Applications of the A* Algorithm. [Internet] [Thesis]. Helsinki University of Technology; 2005. [cited 2021 Apr 14]. Available from: http://lib.tkk.fi/Diss/2005/isbn9512279487/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Autere A. Extensions and Applications of the A* Algorithm. [Thesis]. Helsinki University of Technology; 2005. Available from: http://lib.tkk.fi/Diss/2005/isbn9512279487/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

18. Pentzer, Jesse Lorenzo. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.

Degree: 2014, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/23458

► This dissertation provides details of work completed in the areas of skid-steer robot modeling, trajectory control, power modeling, and energy use prediction. The vast majority… (more)

Subjects/Keywords: ground robotics; robot performance; motion estimation; state estimation; skid-steer robotics; path planning

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APA (6^th Edition):

Pentzer, J. L. (2014). Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/23458

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pentzer, Jesse Lorenzo. “Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.” 2014. Thesis, Penn State University. Accessed April 14, 2021. https://submit-etda.libraries.psu.edu/catalog/23458.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pentzer, Jesse Lorenzo. “Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.” 2014. Web. 14 Apr 2021.

Vancouver:

Pentzer JL. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Apr 14]. Available from: https://submit-etda.libraries.psu.edu/catalog/23458.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pentzer JL. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/23458

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Washington

19. Rajasekaran, Keshav. Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.

Degree: 2017, University of Washington

URL: http://hdl.handle.net/1773/40643

► Automation of an optical tweezers system is critical to fully leverage its immense multiplexing capabilities, which allows for highly precise and reliable manipulation of microscopic… (more)

Subjects/Keywords: Brownian Motion; MPC; Optical Tweezers; Path planning; Stochastic Control; Mechanical engineering; Mechanical engineering

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APA (6^th Edition):

Rajasekaran, K. (2017). Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/40643

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rajasekaran, Keshav. “Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.” 2017. Thesis, University of Washington. Accessed April 14, 2021. http://hdl.handle.net/1773/40643.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rajasekaran, Keshav. “Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.” 2017. Web. 14 Apr 2021.

Vancouver:

Rajasekaran K. Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres. [Internet] [Thesis]. University of Washington; 2017. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1773/40643.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rajasekaran K. Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres. [Thesis]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40643

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Queens University

20. Amiss, David Scott Cameron. Obstructions to Motion Planning by the Continuation Method .

Degree: Chemical Engineering, 2013, Queens University

URL: http://hdl.handle.net/1974/7703

► The subject of this thesis is the motion planning algorithm known as the continuation method. To solve motion planning problems, the continuation method proceeds by… (more)

Subjects/Keywords: geometric control theory ; motion planning ; continuation method ; path-lifting equations ; singular controls ; nonlinear control theory

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APA (6^th Edition):

Amiss, D. S. C. (2013). Obstructions to Motion Planning by the Continuation Method . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/7703

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Amiss, David Scott Cameron. “Obstructions to Motion Planning by the Continuation Method .” 2013. Thesis, Queens University. Accessed April 14, 2021. http://hdl.handle.net/1974/7703.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Amiss, David Scott Cameron. “Obstructions to Motion Planning by the Continuation Method .” 2013. Web. 14 Apr 2021.

Vancouver:

Amiss DSC. Obstructions to Motion Planning by the Continuation Method . [Internet] [Thesis]. Queens University; 2013. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1974/7703.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Amiss DSC. Obstructions to Motion Planning by the Continuation Method . [Thesis]. Queens University; 2013. Available from: http://hdl.handle.net/1974/7703

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Duke University

21. Luo, Xusheng. Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications .

Degree: 2020, Duke University

URL: http://hdl.handle.net/10161/22155

► The study of high-level complex tasks for robotics, captured by temporal logics, e.g., Linear Temporal Logic (LTL), has gained significant research interest in the… (more)

▼ The study of high-level complex tasks for robotics, captured by temporal logics, e.g., Linear Temporal Logic (LTL), has gained significant research interest in the last decade, which extends the traditional point-to-point navigation by incorporating temporal goals. This dissertation proposes and evaluates scalable path planning and control synthesis methods for robotic systems under temporal logic specifications. The scalability is measured by the number of robots, the size of the environment, and the complexity of temporal logic specifications. First, we consider the optimal control synthesis to satisfy the task specified by temporal logic specifications. Given the same discrete workspace, rather than solving a new formula from scratch, we propose a method that exploits experience from solving similar LTL tasks before. The key idea is to decompose complex LTL tasks into simpler subtasks appropriately and define sets of skills, or plans, needed to solve these subtasks. These skills can be stored in a library of reusable skills and can be used to quickly synthesize plans for new tasks that have not been encountered before, meanwhile expanding the library with new skills. We present numerical experiments that show that our approach generally outperforms these methods in terms of time to generate feasible plans. We also show that our proposed algorithm is probabilistically complete and asymptotically optimal. Next, we consider the problem of optimally allocating tasks, expressed as global LTL specifications to teams of heterogeneous mobile robots. The robots are classified in different types that capture their different capabilities in accomplishing tasks, and each task may require robots of multiple types. The specific robots assigned to each task are immaterial, as long as they are of the desired type. Given a discrete workspace, our goal is to design paths, i.e., sequences of discrete states, for the robots so that the LTL specification is satisfied. To obtain a scalable solution to this complex assignment problem, we propose a hierarchical approach that first allocates specific robots to tasks using the information about tasks provided by the Nondeterministic Büchi Automaton (NBA) that captures the LTL specification, and then designs low-level executable plans for the robots that respect the high-level assignment. We provide theoretical results showing completeness and soundness of our proposed method and present numerical simulations demonstrating that our method can generate robot paths with lower cost, considerably faster than existing methods. The majority of existing LTL planning methods rely on the construction of a discrete product automaton that combines a discrete abstraction of robot mobility and the NBA corresponding to the LTL specification. However, constructing expressive discrete abstractions makes the synthesis problem computationally intractable. Finally, we propose a new sampling-based LTL planning algorithm that does not require any discrete abstraction of robot mobility.… Advisors/Committee Members: Zavlanos, Michael M (advisor).

Subjects/Keywords: Robotics; Formal Methods; Motion and Path Planning; Optimization and Optimal Control; Robotics; Task Allocation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Luo, X. (2020). Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/22155

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Luo, Xusheng. “Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications .” 2020. Thesis, Duke University. Accessed April 14, 2021. http://hdl.handle.net/10161/22155.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Luo, Xusheng. “Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications .” 2020. Web. 14 Apr 2021.

Vancouver:

Luo X. Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications . [Internet] [Thesis]. Duke University; 2020. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/10161/22155.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Luo X. Scalable Control Synthesis for Multi-Robot Systems under Temporal Logic Specifications . [Thesis]. Duke University; 2020. Available from: http://hdl.handle.net/10161/22155

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

22. Wang, Sen. Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model.

Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech

URL: http://hdl.handle.net/1853/64143

► Chinese calligraphy is a unique art form with great artistic value but difficult to master. In this thesis, we formulate the calligraphy writing problem as… (more)

Subjects/Keywords: Motion and Path Planning; Optimization and Optimal Control; Modeling, Control, and Learning for Soft Robots

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, S. (2020). Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64143

Chicago Manual of Style (16^th Edition):

Wang, Sen. “Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model.” 2020. Masters Thesis, Georgia Tech. Accessed April 14, 2021. http://hdl.handle.net/1853/64143.

MLA Handbook (7^th Edition):

Wang, Sen. “Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model.” 2020. Web. 14 Apr 2021.

Vancouver:

Wang S. Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1853/64143.

Council of Science Editors:

Wang S. Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64143

University of Michigan

23. Lin, Yu-Chi. Learning for Humanoid Multi-Contact Navigation Planning.

Degree: PhD, Robotics, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/162908

► Humanoids' abilities to navigate uneven terrain make them well-suited for disaster response efforts, but humanoid motion planning in unstructured environments remains a challenging problem. In… (more)

▼ Humanoids' abilities to navigate uneven terrain make them well-suited for disaster response efforts, but humanoid motion planning in unstructured environments remains a challenging problem. In this dissertation we focus on planning contact sequences for a humanoid robot navigating in large unstructured environments using multi-contact motion, including both foot and palm contacts. In particular, we address the two following questions: (1) How do we efficiently generate a feasible contact sequence? and (2) How do we efficiently generate contact sequences which lead to dynamically-robust motions? For the first question, we propose a library-based method that retrieves motion plans from a library constructed offline, and adapts them with local trajectory optimization to generate the full motion plan from the start to the goal. This approach outperforms a conventional graph search contact planner when it is difficult to decide which contact is preferable with a simplified robot model and local environment information. We also propose a learning approach to estimate the difficulty to traverse a certain region based on the environment features. By integrating the two approaches, we propose a planning framework that uses graph search planner to find contact sequences around easy regions. When it is necessary to go through a difficult region, the framework switches to use the library-based method around the region to find a feasible contact sequence faster. For the second question, we consider dynamic motions in contact planning. Most humanoid motion generators do not optimize the dynamic robustness of a contact sequence. By querying a learned model to predict the dynamic feasibility and robustness of each contact transition from a centroidal dynamics optimizer, the proposed planner efficiently finds contact sequences which lead to dynamically-robust motions. We also propose a learning-based footstep planner which takes external disturbances into account. The planner considers not only the poses of the planned contact sequence, but also alternative contacts near the planned contact sequence that can be used to recover from external disturbances. Neural networks are trained to efficiently predict multi-contact zero-step and one-step capturability, which allows the planner to generate contact sequences robust to external disturbances efficiently. Advisors/Committee Members: Berenson, Dmitry (committee member), Johnson-Roberson, Matthew Kai (committee member), Jenkins, Odest Chadwicke (committee member), Righetti, Ludovic (committee member).

Subjects/Keywords: Motion and Path Planning; Humanoid and Bipedal Locomotion; Neural Network; Computer Science; Engineering

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APA (6^th Edition):

Lin, Y. (2020). Learning for Humanoid Multi-Contact Navigation Planning. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/162908

Chicago Manual of Style (16^th Edition):

Lin, Yu-Chi. “Learning for Humanoid Multi-Contact Navigation Planning.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 14, 2021. http://hdl.handle.net/2027.42/162908.

MLA Handbook (7^th Edition):

Lin, Yu-Chi. “Learning for Humanoid Multi-Contact Navigation Planning.” 2020. Web. 14 Apr 2021.

Vancouver:

Lin Y. Learning for Humanoid Multi-Contact Navigation Planning. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/2027.42/162908.

Council of Science Editors:

Lin Y. Learning for Humanoid Multi-Contact Navigation Planning. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/162908

24. Campana, Mylène. Motion planning for digital actors : Planification de mouvements pour acteurs digitaux.

Degree: Docteur es, Robotique, 2017, Université Toulouse III – Paul Sabatier

URL: http://www.theses.fr/2017TOU30097

►

Les algorithmes probabilistes offrent de puissantes possibilités quant à la résolution de problèmes de planification de mouvements pour des robots complexes dans des environnements quelconques.… (more)

▼

Les algorithmes probabilistes offrent de puissantes possibilités quant à la résolution de problèmes de planification de mouvements pour des robots complexes dans des environnements quelconques. Cependant, la qualité des chemins solutions obtenus est discutable. Cette thèse propose un outil pour optimiser ces chemins et en améliorer la qualité. La méthode se base sur l'optimisation numérique contrainte et la détection de collision pour réduire la longueur du chemin tout en évitant les collisions. La modularité des méthodes probabilistes nous a aussi inspirés pour réaliser un algorithme de génération de sauts pour des personnages. Cet algorithme est décrit par trois étapes de planifications, de la trajectoire du centre du personnage jusqu'à son mouvement corps-complet. Chaque étape bénéficie de la rigueur de la planification pour éviter les collisions et pour contraindre le chemin. Nous avons proposé des contraintes inspirées de la physique pour améliorer la plausibilité des mouvements, telles que du non-glissement, de la limitation de vitesse et du maintien de contacts. Les travaux de cette thèse ont été intégrés dans le logiciel "Humanoid Path Planner" et les rendus visuels effectués avec Blender.

Probabilistic algorithms offer powerful possibilities as for solving motion planning problems for complex robots in arbitrary environments. However, the quality of obtained solution paths is questionable. This thesis presents a tool to optimize these paths and improve their quality. The method is based on constrained numerical optimization and on collision checking to reduce the path length while avoiding collisions. The modularity of probabilistic methods also inspired us to design a motion generation algorithm for jumping characters. This algorithm is described by three steps of motion planning, from the trajectory of the character's center to the wholebody motion. Each step benefits from the rigor of motion planning to avoid collisions and to constraint the path. We proposed physics-inspired constraints to increase the plausibility of motions, such as slipping avoidance, velocity limitation and contact maintaining. The thesis works have been implemented in the software `Humanoid Path Planner' and the graphical renderings have been done with Blender.

Advisors/Committee Members: Laumond, Jean-Paul (thesis director).

Subjects/Keywords: Planification de mouvement; Animation graphique; Mouvement ballistique; Optimisation de chemin; Simulation; Motion planning; Computer animation; Ballistic motion; Path optimization; Simulation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Campana, M. (2017). Motion planning for digital actors : Planification de mouvements pour acteurs digitaux. (Doctoral Dissertation). Université Toulouse III – Paul Sabatier. Retrieved from http://www.theses.fr/2017TOU30097

Chicago Manual of Style (16^th Edition):

Campana, Mylène. “Motion planning for digital actors : Planification de mouvements pour acteurs digitaux.” 2017. Doctoral Dissertation, Université Toulouse III – Paul Sabatier. Accessed April 14, 2021. http://www.theses.fr/2017TOU30097.

MLA Handbook (7^th Edition):

Campana, Mylène. “Motion planning for digital actors : Planification de mouvements pour acteurs digitaux.” 2017. Web. 14 Apr 2021.

Vancouver:

Campana M. Motion planning for digital actors : Planification de mouvements pour acteurs digitaux. [Internet] [Doctoral dissertation]. Université Toulouse III – Paul Sabatier; 2017. [cited 2021 Apr 14]. Available from: http://www.theses.fr/2017TOU30097.

Council of Science Editors:

Campana M. Motion planning for digital actors : Planification de mouvements pour acteurs digitaux. [Doctoral Dissertation]. Université Toulouse III – Paul Sabatier; 2017. Available from: http://www.theses.fr/2017TOU30097

KTH

25. Behere, Sagar. A Generic Framework for Robot Motion Planning and Control.

Degree: CAS, 2010, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806

► This thesis deals with the general problem of robot motion planning and control. It proposes the hypothesis that it should bepossible to create a… (more)

Subjects/Keywords: path planning; motion control; software framework; trajectory generation; path constrained motion; obstacle avoidance

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APA (6^th Edition):

Behere, S. (2010). A Generic Framework for Robot Motion Planning and Control. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Behere, Sagar. “A Generic Framework for Robot Motion Planning and Control.” 2010. Thesis, KTH. Accessed April 14, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Behere, Sagar. “A Generic Framework for Robot Motion Planning and Control.” 2010. Web. 14 Apr 2021.

Vancouver:

Behere S. A Generic Framework for Robot Motion Planning and Control. [Internet] [Thesis]. KTH; 2010. [cited 2021 Apr 14]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Behere S. A Generic Framework for Robot Motion Planning and Control. [Thesis]. KTH; 2010. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104806

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Florida International University

26. Zanlongo, Sebastian A. Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning.

Degree: PhD, Computer Science, 2018, Florida International University

URL: https://digitalcommons.fiu.edu/etd/3897 ; FIDC007010

► Large quantities of high-level radioactive waste were generated during WWII. This waste is being stored in facilities such as double-shell tanks in Washington, and… (more)

▼ Large quantities of high-level radioactive waste were generated during WWII. This waste is being stored in facilities such as double-shell tanks in Washington, and the Waste Isolation Pilot Plant in New Mexico. Due to the dangerous nature of radioactive waste, these facilities must undergo periodic inspections to ensure that leaks are detected quickly. In this work, we provide a set of methodologies to aid in the monitoring and inspection of these hazardous facilities. This allows inspection of dangerous regions without a human operator, and for the inspection of locations where a person would not be physically able to enter. First, we describe a robot equipped with sensors which uses a modified A* path-planning algorithm to navigate in a complex environment with a tether constraint. This is then augmented with an adaptive informative path planning approach that uses the assimilated sensor data within a Gaussian Process distribution model. The model's predictive outputs are used to adaptively plan the robot's path, to quickly map and localize areas from an unknown field of interest. The work was validated in extensive simulation testing and early hardware tests. Next, we focused on how to assign tasks to a heterogeneous set of robots. Task assignment is done in a manner which allows for task-robot dependencies, prioritization of tasks, collision checking, and more realistic travel estimates among other improvements from the state-of-the-art. Simulation testing of this work shows an increase in the number of tasks which are completed ahead of a deadline. Finally, we consider the case where robots are not able to complete planned tasks fully autonomously and require operator assistance during parts of their planned trajectory. We present a sampling-based methodology for allocating operator attention across multiple robots, or across different parts of a more sophisticated robot. This allows few operators to oversee large numbers of robots, allowing for a more scalable robotic infrastructure. This work was tested in simulation for both multi-robot deployment, and high degree-of-freedom robots, and was also tested in multi-robot hardware deployments. The work here can allow robots to carry out complex tasks, autonomously or with operator assistance. Altogether, these three components provide a comprehensive approach towards robotic deployment within the deactivation and decommissioning tasks faced by the Department of Energy. Advisors/Committee Members: Leonardo Bobadilla, Mark Finlayson, Monique Ross, Ning Xie, Dwayne McDaniel.

Subjects/Keywords: robotics; motion planning; human-robot-interaction; scheduling; coordination; path-planning; decommissioning; inspection; Artificial Intelligence and Robotics; Other Computer Sciences; Robotics

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APA (6^th Edition):

Zanlongo, S. A. (2018). Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning. (Doctoral Dissertation). Florida International University. Retrieved from https://digitalcommons.fiu.edu/etd/3897 ; FIDC007010

Chicago Manual of Style (16^th Edition):

Zanlongo, Sebastian A. “Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning.” 2018. Doctoral Dissertation, Florida International University. Accessed April 14, 2021. https://digitalcommons.fiu.edu/etd/3897 ; FIDC007010.

MLA Handbook (7^th Edition):

Zanlongo, Sebastian A. “Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning.” 2018. Web. 14 Apr 2021.

Vancouver:

Zanlongo SA. Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning. [Internet] [Doctoral dissertation]. Florida International University; 2018. [cited 2021 Apr 14]. Available from: https://digitalcommons.fiu.edu/etd/3897 ; FIDC007010.

Council of Science Editors:

Zanlongo SA. Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning. [Doctoral Dissertation]. Florida International University; 2018. Available from: https://digitalcommons.fiu.edu/etd/3897 ; FIDC007010

Georgia Tech

27. Cowlagi, Raghvendra V. Hierarchical motion planning for autonomous aerial and terrestrial vehicles.

Degree: PhD, Aerospace Engineering, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/41066

► Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian… (more)

Subjects/Keywords: Multi-resolution; Motion planning; Robotics; Vehicle dynamics; Graph search; Curvature bounded path planning; Autonomous vehicles; Mobile robots; Robots; Autonomous robots

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cowlagi, R. V. (2011). Hierarchical motion planning for autonomous aerial and terrestrial vehicles. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/41066

Chicago Manual of Style (16^th Edition):

Cowlagi, Raghvendra V. “Hierarchical motion planning for autonomous aerial and terrestrial vehicles.” 2011. Doctoral Dissertation, Georgia Tech. Accessed April 14, 2021. http://hdl.handle.net/1853/41066.

MLA Handbook (7^th Edition):

Cowlagi, Raghvendra V. “Hierarchical motion planning for autonomous aerial and terrestrial vehicles.” 2011. Web. 14 Apr 2021.

Vancouver:

Cowlagi RV. Hierarchical motion planning for autonomous aerial and terrestrial vehicles. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1853/41066.

Council of Science Editors:

Cowlagi RV. Hierarchical motion planning for autonomous aerial and terrestrial vehicles. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/41066

University of Maryland

28. Shah, Brual. Planning for Autonomous Operation of Unmanned Surface Vehicles.

Degree: Mechanical Engineering, 2016, University of Maryland

URL: http://hdl.handle.net/1903/19040

► The growing variety and complexity of marine research and application oriented tasks requires unmanned surface vehicles (USVs) to operate fully autonomously over long time horizons… (more)

▼ The growing variety and complexity of marine research and application oriented tasks requires unmanned surface vehicles (USVs) to operate fully autonomously over long time horizons even in environments with significant civilian traffic. The autonomous operations of the USV over long time horizons requires a path planner to compute paths over long distances in complex marine environments consisting of hundreds of islands of complex shapes. The available free space in marine environment changes over time as a result of tides, environmental restrictions, and weather. Secondly, the maximum velocity and energy consumption of the USV is significantly influenced by the fluid medium flows such as strong currents. Finally, the USV have to operate in an unfamiliar, unstructured marine environment with obstacles of variable dimensions, shapes, and motion dynamics such as other unmanned surface vehicles, civilian boats, shorelines, or docks poses numerous planning challenges. The proposed Ph.D. dissertation explores the above mentioned problems by developing computationally efficient path and trajectory planning algorithms that enables the long term autonomous operation of the USVs. We have developed a lattice-based 5D trajectory planner for the USVs operating in the environment with the congested civilian traffic. The planner estimates collision risk and reasons about the availability of contingency maneuvers to counteract unpredictable behaviors of civilian vessels. Secondly, we present a computationally efficient and optimal algorithm for long distance path planning in complex marine environments using A* search on visibility graphs defined over quad trees. Finally, we present an A* based path planning algorithm with newly developed admissible heuristics for computing energy efficient paths in environment with significant fluid flows. The effectiveness of the planning algorithms is demonstrated in the simulation environments by using systems identified dynamics model of the wave amplitude modular vessel (WAM-V) USV14. Advisors/Committee Members: Gupta, Satyandra K (advisor).

Subjects/Keywords: Robotics; Mechanical engineering; Ocean engineering; Autonomy; Marine Vehicles; Motion Planning; Path Planning; Robotics; Unmanned Surface Vehicles

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APA (6^th Edition):

Shah, B. (2016). Planning for Autonomous Operation of Unmanned Surface Vehicles. (Thesis). University of Maryland. Retrieved from http://hdl.handle.net/1903/19040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shah, Brual. “Planning for Autonomous Operation of Unmanned Surface Vehicles.” 2016. Thesis, University of Maryland. Accessed April 14, 2021. http://hdl.handle.net/1903/19040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shah, Brual. “Planning for Autonomous Operation of Unmanned Surface Vehicles.” 2016. Web. 14 Apr 2021.

Vancouver:

Shah B. Planning for Autonomous Operation of Unmanned Surface Vehicles. [Internet] [Thesis]. University of Maryland; 2016. [cited 2021 Apr 14]. Available from: http://hdl.handle.net/1903/19040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shah B. Planning for Autonomous Operation of Unmanned Surface Vehicles. [Thesis]. University of Maryland; 2016. Available from: http://hdl.handle.net/1903/19040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Berg, J.P. van den. Path planning in dynamic environments.

Degree: 2007, University Utrecht

URL: https://dspace.library.uu.nl/handle/1874/20873 ; URN:NBN:NL:UI:10-1874-20873 ; 1874/20873 ; urn:isbn:9789039344804 ; URN:NBN:NL:UI:10-1874-20873 ; https://dspace.library.uu.nl/handle/1874/20873

► Path planning plays an important role in various fields of application, such as CAD design, computer games and virtual environments, molecular biology, and robotics. In… (more)

Subjects/Keywords: robotics; computational geometry; path planning; motion planning; dynamic environments

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APA (6^th Edition):

Berg, J. P. v. d. (2007). Path planning in dynamic environments. (Doctoral Dissertation). University Utrecht. Retrieved from https://dspace.library.uu.nl/handle/1874/20873 ; URN:NBN:NL:UI:10-1874-20873 ; 1874/20873 ; urn:isbn:9789039344804 ; URN:NBN:NL:UI:10-1874-20873 ; https://dspace.library.uu.nl/handle/1874/20873

Chicago Manual of Style (16^th Edition):

Berg, J P van den. “Path planning in dynamic environments.” 2007. Doctoral Dissertation, University Utrecht. Accessed April 14, 2021. https://dspace.library.uu.nl/handle/1874/20873 ; URN:NBN:NL:UI:10-1874-20873 ; 1874/20873 ; urn:isbn:9789039344804 ; URN:NBN:NL:UI:10-1874-20873 ; https://dspace.library.uu.nl/handle/1874/20873.

MLA Handbook (7^th Edition):

Berg, J P van den. “Path planning in dynamic environments.” 2007. Web. 14 Apr 2021.

Vancouver:

Berg JPvd. Path planning in dynamic environments. [Internet] [Doctoral dissertation]. University Utrecht; 2007. [cited 2021 Apr 14]. Available from: https://dspace.library.uu.nl/handle/1874/20873 ; URN:NBN:NL:UI:10-1874-20873 ; 1874/20873 ; urn:isbn:9789039344804 ; URN:NBN:NL:UI:10-1874-20873 ; https://dspace.library.uu.nl/handle/1874/20873.

Council of Science Editors:

Berg JPvd. Path planning in dynamic environments. [Doctoral Dissertation]. University Utrecht; 2007. Available from: https://dspace.library.uu.nl/handle/1874/20873 ; URN:NBN:NL:UI:10-1874-20873 ; 1874/20873 ; urn:isbn:9789039344804 ; URN:NBN:NL:UI:10-1874-20873 ; https://dspace.library.uu.nl/handle/1874/20873

30. Ma, Yingchong. Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots.

Degree: Docteur es, Automatique, génie informatique, traitement du signal et images, 2013, Ecole centrale de Lille

URL: http://www.theses.fr/2013ECLI0025

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Ce travail propose de nouvelles stratégies pour la planification et le contrôle des robots mobiles non-holonomes, de nouveaux algorithmes sont proposés. Tout d'abord, l'identification des… (more)

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Ce travail propose de nouvelles stratégies pour la planification et le contrôle des robots mobiles non-holonomes, de nouveaux algorithmes sont proposés. Tout d'abord, l'identification des différents modèles cinématiques de robot mobiles est discutée, et le problème est formulé comme l'identification en temps réel du signal de commutation d'un système singulier non-linéaire et à commutation. Deuxièmement, sur la base du modèle identifié, un algorithme de planification locale est proposé, et le contour irrégulier de l' obstacle est représenté par des segments. La trajectoire est obtenue en résolvant un problème de commande optimale avec contraintes. Troisièmement, nous appliquons un contrôleur i-PID pour contrôler le robot mobile non-holonome avec la perturbation dans les mesures. Un paramètre de commutation α est proposé en raison de la particularité du système non-holonome. En plus de notre algorithme de planification proposé, une autre approche de planification en utilisant de champs de potentiels est proposée. La nouvelle fonction de champ de potentiel est en mesure de résoudre les problèmes de minima locaux et de produire des forces lisses pour éviter les oscillations. Enfin, une approche de planification coopérative entre robots est proposée en utilisant les informations locales partagées par chaque robot. Le graphe de visibilité est utilisé pour générer une série d'objectifs intermédiaires qui assureront aux robots d’atteindre l'objectif final, et un algorithme est proposé pour étendre les obstacles et fusionner les obstacles lorsque deux obstacles s'entrecroisent

This PhD thesis is dedicated to the path planning and control strategy for non-holonomic mobile robots. After a review of the recent researches and their features, new path planning algorithms and control strategies are proposed. Firstly, the identification of different mobile robot kinematic models is discussed, robot kinematic models are formulated as a switched singular nonlinear system, and the problem becomes the real-time identification of the switching signal. Secondly, based on the identified model, a local path planning algorithm is proposed, in which the irregular contour of obstacles is represented by segments. The path planning problem is formulated as a constrained receding horizon planning problem and the trajectory is obtained by solving an optimal control problem with constraints. Thirdly, we apply an i-PID controller to control the non-holonomic mobile robot with measurement disturbance. A switching parameter α is proposed because of the particularity of the non-holonomic system. In addition to our proposed path planning algorithm, another path planning approach using potential field is proposed. The modified potential field function, which takes into account the robot orientation and angular velocity, is able to solve local minima problems and produce smooth forces to avoid oscillations. Finally, a cooperative path planning approach between robots is proposed by using the shared local information of each robot. The visibility graph…

Advisors/Committee Members: Perruquetti, Wilfrid (thesis director), Zheng, Gang (thesis director).

Subjects/Keywords: Robots mobiles non -holonomes; Planification; La commande du mouvement; Fonction potentiel; Planification coopérative; Non-holonomic mobile robot; Path Planning; Motion control; Potential field function; Cooperative path planning; 620

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APA (6^th Edition):

Ma, Y. (2013). Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots. (Doctoral Dissertation). Ecole centrale de Lille. Retrieved from http://www.theses.fr/2013ECLI0025

Chicago Manual of Style (16^th Edition):

Ma, Yingchong. “Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots.” 2013. Doctoral Dissertation, Ecole centrale de Lille. Accessed April 14, 2021. http://www.theses.fr/2013ECLI0025.

MLA Handbook (7^th Edition):

Ma, Yingchong. “Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots.” 2013. Web. 14 Apr 2021.

Vancouver:

Ma Y. Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots. [Internet] [Doctoral dissertation]. Ecole centrale de Lille; 2013. [cited 2021 Apr 14]. Available from: http://www.theses.fr/2013ECLI0025.

Council of Science Editors:

Ma Y. Planification de trajectoire et commande pour les robots mobiles non-holonomes : Path planning and control of non-holonomic mobile robots. [Doctoral Dissertation]. Ecole centrale de Lille; 2013. Available from: http://www.theses.fr/2013ECLI0025

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