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Georgia Tech
1.
Shukla, Ayush.
Reinforcement learning based active localization for precise manipulation.
Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/62712 
► Precision during positioning of a robot arm is inherently limited by the sensing capabilities of the robot. In the case of fully on-board sensing, this…
(more)
▼ Precision during positioning of a robot arm is inherently limited by the sensing capabilities of the robot. In the case of fully on-board sensing, this limitation is further exacerbated by inconsistencies in the expected and actual structure of the robot environment. Further, precision is also affected by uncertainty in the estimate of the robot pose. While these sources of errors can never be fully eliminated, we can at least devise an optimal measurement policy for a given sensor configuration and robot environment. That is exactly what we try to do in this thesis. Such a policy would ensure that measurements are taken from places which lead to an optimal increase the localisation precision. For our purpose, we assume that the robot end-effector is equipped with a sensor setup consisting of an array of highly accurate 1D laser rangefinders (pointlasers). Pointlasers provide a cheaper and more accurate alternative to a 3D LiDAR, at the expense of measurements which are sparsely distributed in the rotation space. We treat this policy estimation problem as an active localization problem and set up a 3D simulation environment consisting of the CAD model of a building. Inside this environment, we simulate different orientations of the pointlaser array and train a reinforcement learning (RL) agent which predicts the best orientation for a given position in the CAD model. Using reduction in uncertainty (information gain) as the reward, we come up with a policy which takes reliable measurements and thus, should lead to precise positioning of the end-effector. We train the agent using an on-policy RL algorithm and present the results on a number of test CAD models.
Advisors/Committee Members: Pradalier, Cedric (advisor), Voss, Paul (committee member), Coogan, Samuel (committee member).
Subjects/Keywords: Reinforcement learning; Robotics; Manipulation; Active localization
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APA (6th Edition):
Shukla, A. (2020). Reinforcement learning based active localization for precise manipulation. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62712
Chicago Manual of Style (16th Edition):
Shukla, Ayush. “Reinforcement learning based active localization for precise manipulation.” 2020. Masters Thesis, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/62712.
MLA Handbook (7th Edition):
Shukla, Ayush. “Reinforcement learning based active localization for precise manipulation.” 2020. Web. 27 Feb 2021.
Vancouver:
Shukla A. Reinforcement learning based active localization for precise manipulation. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/62712.
Council of Science Editors:
Shukla A. Reinforcement learning based active localization for precise manipulation. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62712
Georgia Tech
2.
Zhong, Hai.
Congestion game-based task allocation for multi-robot teams.
Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/62843
► Multi-robot teams can complete complex missions that are not amenable to an individual robot. A team of heterogeneous robots with complementing capabilities is endowed with…
(more)
▼ Multi-robot teams can complete complex missions that are not amenable to an individual robot. A team of heterogeneous robots with complementing capabilities is endowed with advantages to allow deep collaboration in dynamic and complicated environments. Multi-robot Task Allocation (MRTA) presents a fundamental for multi-robot system research. Despite the previous research efforts, there remains a knowledge gap in developing decentralized approaches for MRTA by viewing robots as resources and optimizing the distribution of robots to achieve the best overall performance at the system level. To address this knowledge gap, the objective of this research is to develop decentralized resource allocation algorithms to provide approximate solutions for the MRTA problem. Both standard congestion game theory and weighted congestion game theory are exploited as the theoretical framework to formulate and solve the MRTA problems. Two types of resource allocation problems are considered, one has increasing marginal gain with respect to the number of participating robots, the other has decreasing marginal gain with respect to the number of participating robots. For MRTA problems with homogeneous robot teams, the sequential best response dynamics is integrated in the framework of standard congestion game theory. A concurrent version of best response dynamics with convergence guarantees is developed. In addition, a decentralized dual greedy algorithm is proposed and its convergence to a pure Nash equilibrium is proved. For MRTA problems with heterogeneous robot teams, the best sequential dynamics is shown to converge to pure Nash equilibrium in the framework of weighted congestion games. The suboptimality of the approximate solutions is discussed by λ-μ smoothness technique. Simulations and experiments using robots in the Robotarium are conducted to validate the effectiveness of the proposed algorithms.
Advisors/Committee Members: Hutchinson, Seth (advisor), Coogan, Samuel (committee member), Vamvoudakis, Kyriakos (committee member).
Subjects/Keywords: Multi-robot systems; Task allocation; Congestion games
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APA (6th Edition):
Zhong, H. (2020). Congestion game-based task allocation for multi-robot teams. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62843
Chicago Manual of Style (16th Edition):
Zhong, Hai. “Congestion game-based task allocation for multi-robot teams.” 2020. Masters Thesis, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/62843.
MLA Handbook (7th Edition):
Zhong, Hai. “Congestion game-based task allocation for multi-robot teams.” 2020. Web. 27 Feb 2021.
Vancouver:
Zhong H. Congestion game-based task allocation for multi-robot teams. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/62843.
Council of Science Editors:
Zhong H. Congestion game-based task allocation for multi-robot teams. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62843
Georgia Tech
3.
Mains, John B.
Scheduling and assignment on dynamic processor networks.
Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/63680
► We address the problem of scheduling tasks characterized by dynamic completion time behavior. Existing scheduling methodologies reduce problems to using constant task durations and are…
(more)
▼ We address the problem of scheduling tasks characterized by dynamic completion time behavior. Existing scheduling methodologies reduce problems to using constant task durations and are therefore not suitable for problems with more complex completion time behavior. One such problem is scheduling applications on computer networks with time-varying communication channel capacities. We present a methodology that can be used to solve such problems. The specific contributions of this work are: (a) a novel representation for the completion time of tasks in scheduling problems, (b) a method for approximating that representation efficiently using an affine over-approximation, and (c) a mixed-integer programming-based formulation to solve a variety of scheduling problems using this representation and approximation. The resulting framework can be used to solve scheduling problems with time-varying task durations, and thus solve problems with time-varying communication links or resources. A case study is provided, in which we devise a scheduling scheme for computation on a computer network composed of processors onboard a satellite constellation. This example is an instance of scheduling applications on computer networks with known time-varying communication channel capacities and the results of the case study demonstrate the improvement of using the approximation method over existing methods.
Advisors/Committee Members: Feron, Eric (advisor), Coogan, Samuel (committee member), Bloch, Matthieu (committee member).
Subjects/Keywords: Multiprocessor scheduling; Time-varying duration; Satellite constellations; Mixed-integer programming
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APA (6th Edition):
Mains, J. B. (2020). Scheduling and assignment on dynamic processor networks. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63680
Chicago Manual of Style (16th Edition):
Mains, John B. “Scheduling and assignment on dynamic processor networks.” 2020. Masters Thesis, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/63680.
MLA Handbook (7th Edition):
Mains, John B. “Scheduling and assignment on dynamic processor networks.” 2020. Web. 27 Feb 2021.
Vancouver:
Mains JB. Scheduling and assignment on dynamic processor networks. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/63680.
Council of Science Editors:
Mains JB. Scheduling and assignment on dynamic processor networks. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63680
Georgia Tech
4.
Dutreix, Maxence Dominique Henri.
Verification and synthesis for stochastic systems with temporal logic specifications.
Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/62820
► The objective of this thesis is to first provide a formal framework for the verification of discrete-time, continuous-space stochastic systems with complex temporal specifications. Secondly,…
(more)
▼ The objective of this thesis is to first provide a formal framework for the verification of discrete-time, continuous-space stochastic systems with complex temporal specifications. Secondly, the approach developed for verification is extended to the synthesis of controllers that aim to maximize or minimize the probability of occurrence of temporal behaviors in stochastic systems. As these problems are generally undecidable or intractable to solve, approximation methods are employed in the form of finite-state abstractions arising from a partition of the original system’s domain for which analysis is greatly simplified. The abstractions of choice in this work are Interval-valued Markov Chains (IMC) which, unlike conventional discrete-time Markov Chains, allow for a non-deterministic range of probabilities of transition between states instead of a fixed probability. Techniques for constructing IMC abstractions for two classes of systems are presented. Due to their inherent structure that facilitates estimations of reachable sets, mixed monotone systems with additive disturbances are shown to be efficiently amenable to IMC abstractions. Then, an abstraction procedure for polynomial systems that uses stochastic barrier functions computed via Sum-of-Squares programming is derived. Next, an algorithm for computing satisfaction bounds in IMCs with respect to so-called omega-regular properties is detailed. As probabilistic specifications require finding the set of initial states whose probability of fulfilling some behavior is below or above a certain threshold, this method may yield a set of states whose satisfaction status is undecided. An iterative specification-guided partition refinement method is proposed to reduce conservatism in the abstraction until a precision threshold is met. Finally, similar interval-based finite abstractions are utilized to synthesize control policies for omega-regular objectives in systems with both a finite number of modes and a continuous set of available inputs. A notion of optimality for these policies is introduced and a partition refinement scheme is presented to reach a desired level of optimality.
Advisors/Committee Members: Coogan, Samuel (advisor), Zhang, Fumin (committee member), Zhao, Ye (committee member), Wardi, Yorai (committee member), Vamvoudakis, Kyriakos (committee member).
Subjects/Keywords: Stochastic systems; Model checking; Finite-state abstractions; Temporal logic; Interval-valued markov chain
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APA (6th Edition):
Dutreix, M. D. H. (2020). Verification and synthesis for stochastic systems with temporal logic specifications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62820
Chicago Manual of Style (16th Edition):
Dutreix, Maxence Dominique Henri. “Verification and synthesis for stochastic systems with temporal logic specifications.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/62820.
MLA Handbook (7th Edition):
Dutreix, Maxence Dominique Henri. “Verification and synthesis for stochastic systems with temporal logic specifications.” 2020. Web. 27 Feb 2021.
Vancouver:
Dutreix MDH. Verification and synthesis for stochastic systems with temporal logic specifications. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/62820.
Council of Science Editors:
Dutreix MDH. Verification and synthesis for stochastic systems with temporal logic specifications. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62820
Georgia Tech
5.
You, Changxi.
Autonomous aggressive driving: theory & experiments.
Degree: PhD, Department, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/62872
► Autonomous vehicles represent a major trend in future intelligent transportation systems. In order to develop autonomous vehicles, this dissertation intends to understand expert driving maneuvers…
(more)
▼ Autonomous vehicles represent a major trend in future intelligent transportation systems. In order to develop autonomous vehicles, this dissertation intends to understand expert driving maneuvers in different scenarios such as highway overtaking and off-road rally racing, which are referred to as ``aggressive'' driving in the context of this dissertation. By mimicking expert driving styles, one expects to be able to improve the vehicle's active safety and traffic efficiency in the development of autonomous vehicles. This dissertation starts from the system modeling, namely, driver modeling, vehicle modeling and traffic system modeling, for which we implement different Kalman type filters for nonlinear parameter estimation using experimental data. We then focus on the optimal decision making, path planning and control design problems for highway overtaking and off-road autonomous rally racing, respectively. We propose to use a stochastic MDP for highway traffic modeling. The new concept of ``dynamic cell'' is introduced to dynamically extract the essential state of the traffic according to different vehicle velocities, driver intents (i.e., lane-switching, braking, etc.) and sizes of the surrounding vehicles (i.e., truck, sedan, etc.). This allows us to solve the (inverse) reinforcement learning problem efficiently since the dimensionality of the state space can be maintained in a manageable level. New path planning algorithms using Bezier curves are proposed to generate everywhere 𝐶2 continuous curvature-constrained paths for highway real-time lane-switching. We demonstrate expert overtaking maneuver by implementing the proposed decision making, path planning and control algorithms on an in-house developed traffic simulator. Based on the trajectory learning result, we model high-speed cornering with a segment of steady-state cornering for off-road rally racing. We then propose a geometry-based trajectory planning algorithm using the vehicle's differential flatness. This approach avoids solving optimal control problems on-the-fly, while guaranteeing good racing performance in off-road racing.
Advisors/Committee Members: Tsiotras, Panagiotis (advisor), Feron, Eric Marie J. (committee member), Feigh, Karen (committee member), Boots, Byron (committee member), Coogan, Samuel (committee member), names.
Subjects/Keywords: Autonomous vehicle path; Path planning; System identification; Decision making; Overtaking; Rally racing
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APA (6th Edition):
You, C. (2020). Autonomous aggressive driving: theory & experiments. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62872
Chicago Manual of Style (16th Edition):
You, Changxi. “Autonomous aggressive driving: theory & experiments.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/62872.
MLA Handbook (7th Edition):
You, Changxi. “Autonomous aggressive driving: theory & experiments.” 2020. Web. 27 Feb 2021.
Vancouver:
You C. Autonomous aggressive driving: theory & experiments. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/62872.
Council of Science Editors:
You C. Autonomous aggressive driving: theory & experiments. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62872
Georgia Tech
6.
Boidot, Emmanuel.
Ambush games in discrete and continuous environments.
Degree: PhD, Aerospace Engineering, 2017, Georgia Tech
URL: http://hdl.handle.net/1853/59244
► We consider an autonomous navigation problem, whereby a traveler aims at traversing an environment in which an adversary sets an ambush. A two players zero-…
(more)
▼ We consider an autonomous navigation problem, whereby a traveler aims at traversing an environment in which an adversary sets an ambush. A two players zero- sum game is introduced, describing the initial strategy of the traveler and the ambusher based on a description of the environment and the traveler initial location and desired goal. The process is single-step in the sense that agents do not reevaluate their strategy after the traveler has started moving. Players’ strategies are computed as probabilistic path distributions, a realization of which is the path chosen by the traveler and the ambush location chosen by the ambusher. A parallel is drawn between the discrete problem, where the traveler moves on a network, and the continuous problem, where the traveler moves in a compact subset of R2. Analytical optimal policies are derived. Assumptions from the Minimal Cut - Maximal Flow literature for continuous domains are used. The optimal value of the game is shown to be related to the maximum flow on the environment for sub-classes of games where the reward function for the ambusher is uniform. This proof is detailed in the discrete and continuous setups. In order to relax the assumptions for the computation of the players’ optimal strategies, a sampling-based approach is proposed, inspired by re- cent sampling-based motion planning techniques. Given a uniform reward function for the ambusher, optimal strategies of the sampled ambush game are proven to converge to the optimal strategy of the continuous ambush game under some sampling and connectivity constraints. A linear program is introduced that allows for the computation of optimal policies. The sampling-based approach is more general in the sense that it is compatible with constrained motion primitives for the traveler and non-uniform reward functions for the ambusher. The sampling-based game is used to create example applications for situ- ations where no analytic solution of the Continuous Ambush Game have been identified.This leads to more interesting games, applicable to real-world robots using modern motion planning algorithms. Examples of such games are setups where the traveler’s motion satis- fies Dubins’ kinematic constraints and setups where the reach of the ambusher is dependent on the speed of the traveler.
Advisors/Committee Members: Feron, Eric (advisor), Tsiotras, Panagiotis (committee member), Clarke, John-Paul (committee member), Johnson, Eric (committee member), Coogan, Samuel (committee member).
Subjects/Keywords: Ambush games; Game theory; Motion planning; Continuous flow theory; Sampling-based motion planning
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APA (6th Edition):
Boidot, E. (2017). Ambush games in discrete and continuous environments. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59244
Chicago Manual of Style (16th Edition):
Boidot, Emmanuel. “Ambush games in discrete and continuous environments.” 2017. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/59244.
MLA Handbook (7th Edition):
Boidot, Emmanuel. “Ambush games in discrete and continuous environments.” 2017. Web. 27 Feb 2021.
Vancouver:
Boidot E. Ambush games in discrete and continuous environments. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/59244.
Council of Science Editors:
Boidot E. Ambush games in discrete and continuous environments. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59244
Georgia Tech
7.
Al Abri, Said Salim Hamdan S.
A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING.
Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech
URL: http://hdl.handle.net/1853/63530
► Modeling and control of multi-agent systems is an important problem due to its large variety of potential applications and increasing practical and theoretical challenges. A…
(more)
▼ Modeling and control of multi-agent systems is an important problem due to its large variety of potential applications and increasing practical and theoretical challenges. A large
part of inspiration for modeling and control of multi-agent systems originates from the study of natural collective behaviors observed for example in schools of fish, flocks of
birds, colonies of ants and cultures of bacteria. While individuals in these natural swarms are collectively performing complex tasks such as foraging or synchronization, critical information such as predator warnings propagate across the swarm almost instantly and presumably without explicit communication between the individuals.
On the other hand, algorithms for multi-agent systems to locate a source or to follow a desired level curve of spatially distributed scalar fields generally require sharing field
measurements among the agents for gradient estimation. The dependence on the exchange of data through a communication channel is a hard requirement that might be undesired
especially in applications with severe limitations such as underwater robotics.
The main contribution of this Dissertation is a Multi-Layer control model composed of an interplay of decentralized algorithms for perception and swarming. In the perception
layer, each agent applies a Principal Component Analysis (PCA) on the relative positions and headings of its neighbors to learn principal properties about the motion and the geometry
of the spatial distribution of the surrounding agents. These principal components are then used in the swarming layer where various distributed control laws are designed to balance between achieving a collective task and at the same time allowing critical emerging
signals to propagate to the entire swarm.
Within this Multi-Layer model, we contributed distributed control laws for swarms to perform collective source seeking and level curve tracking of scalar fields. These control
laws scale to swarms of various sizes and graph structures and do not rely on explicitly estimating the field gradient or explicitly sharing measurements among the agents.
Additionally, we contributed a distributed control law that balances between achieving a collective task and at the same time allowing critical signals to propagate to the entire swarm. Through this, we demonstrated implicit information propagation in swarms exhibiting predator-avoidance behavior using only local interactions and without explicit communication or prescribed formations. Moreover, we obtained various stability results
reflecting the convergence and robustness of the proposed algorithms. Finally, we validated the proposed model for source seeking, level curve tracking and predator avoidance
behaviors through various simulation and experimental results. The proposed control model offers a new method that enables robots with limited resources to perform diverse swarming activities with only local information. Additionally, designing analytical models to understand information propagation will not only reveal…
Advisors/Committee Members: Zhang, Fumin (advisor), Egerstedt, Magnus (committee member), Wardi, Yorai (committee member), Coogan, Samuel (committee member), Tao, Molei (committee member).
Subjects/Keywords: multi-agent control; bio-inspired swarm control; source seeking; level curve tracking; information propagation
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APA (6th Edition):
Al Abri, S. S. H. S. (2019). A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63530
Chicago Manual of Style (16th Edition):
Al Abri, Said Salim Hamdan S. “A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING.” 2019. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/63530.
MLA Handbook (7th Edition):
Al Abri, Said Salim Hamdan S. “A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING.” 2019. Web. 27 Feb 2021.
Vancouver:
Al Abri SSHS. A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/63530.
Council of Science Editors:
Al Abri SSHS. A MULTI-LAYER SWARM CONTROL MODEL FOR INFORMATION PROPAGATION AND MULTI-TASKING. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/63530
Georgia Tech
8.
Santos Fernandez, Maria Teresa.
Coverage control: From heterogeneous robot teams to expressive swarms.
Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/63690
► Coverage control constitutes a canonical multi-robot coordination strategy that allows a collection of robots to distribute themselves over a domain to optimally monitor the relevant…
(more)
▼ Coverage control constitutes a canonical multi-robot coordination strategy that allows a collection of robots to distribute themselves over a domain to optimally monitor the relevant features of the environment. This thesis examines two different aspects of the coverage problem. On the one hand, we investigate how coverage should be performed by a multi-robot team with heterogeneous sensor equipment in the presence of qualitatively different types of events or features in the domain, which may evolve over time. To this end, different information exchange strategies among the robots are considered, and the performance of the resulting distributed control laws is compared experimentally on a team of mobile robots. In addition, we present a constraint-based approach that allows the multi-robot team to cover different types of features whose locations in the domain may evolve other time. On the other hand, in the context of swarm robotics in the arts, this thesis investigates how the coverage paradigm, which affords the control of the entire multi-robot team through the high-level specification of density functions, can serve as an effective interaction modality for artists to effectively utilize robotic swarms in different forms of art expression. In particular, we explore the use of coverage, along with other standard multi-robot control algorithms, to create emotionally expressive behaviors for robot theatre applications. Furthermore, the heterogeneous coverage framework developed in this thesis is employed to interactively control desired concentrations of color throughout a canvas for the purpose of artistic multi-robot painting.
Advisors/Committee Members: Egerstedt, Magnus (advisor), Hutchinson, Seth (committee member), Howard, Ayanna (committee member), Coogan, Samuel (committee member), Kumar, Vijay (committee member).
Subjects/Keywords: Robotics; Systems and controls; Swarm robotics; Heterogeneous multi-robot systems; Robots and arts
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APA (6th Edition):
Santos Fernandez, M. T. (2020). Coverage control: From heterogeneous robot teams to expressive swarms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63690
Chicago Manual of Style (16th Edition):
Santos Fernandez, Maria Teresa. “Coverage control: From heterogeneous robot teams to expressive swarms.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/63690.
MLA Handbook (7th Edition):
Santos Fernandez, Maria Teresa. “Coverage control: From heterogeneous robot teams to expressive swarms.” 2020. Web. 27 Feb 2021.
Vancouver:
Santos Fernandez MT. Coverage control: From heterogeneous robot teams to expressive swarms. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/63690.
Council of Science Editors:
Santos Fernandez MT. Coverage control: From heterogeneous robot teams to expressive swarms. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63690
Georgia Tech
9.
Notomista, Gennaro.
Long-duration robot autonomy: From control algorithms to robot design.
Degree: PhD, Mechanical Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/63700
► The transition that robots are experiencing from controlled and often static working environments to unstructured and dynamic settings is unveiling the potential fragility of the…
(more)
▼ The transition that robots are experiencing from controlled and often static working environments to unstructured and dynamic settings is unveiling the potential fragility of
the design and control techniques employed to build and program them, respectively. A paramount of example of a discipline that, by construction, deals with robots operating under
unknown and ever-changing conditions is long-duration robot autonomy. In fact, during long-term deployments, robots will find themselves in environmental scenarios which were not planned and accounted for during the design phase. These operating conditions offer a variety of challenges which are not encountered in any other discipline of robotics. This thesis presents control-theoretic techniques and mechanical design principles to be employed while conceiving, building, and programming robotic systems meant to remain operational over sustained amounts of time. Long-duration autonomy is studied and analyzed from two different, yet complementary, perspectives: control algorithms and robot design. In the context of the former, the persistification of robotic tasks is presented. This consists of an optimization-based control framework which allows robots to remain operational over time horizons that are much longer than the ones which would be allowed by the limited
resources of energy with which they can ever be equipped. As regards the mechanical design aspect of long-duration robot autonomy, in the second part of this thesis, the SlothBot, a slow-paced solar-powered wire-traversing robot, is presented. This robot embodies the design principles required by an autonomous robotic system 1in order to remain functional for truly long periods of time, including energy efficiency, design simplicity, and fail-safeness. To conclude, the development of a robotic platform which stands at the intersection of design and control for long-duration autonomy is described. A class of vibration-driven robots, the brushbots, are analyzed both from a mechanical design perspective, and in terms of interaction control capabilities with the environment in which they are deployed.
Advisors/Committee Members: Egerstedt, Magnus (advisor), Book, Wayne (committee member), Coogan, Samuel (committee member), Hutchinson, Seth (committee member), Mazumdar, Anirban (committee member), Schwager, Mac (committee member).
Subjects/Keywords: Robotics; Control theory; Long-term robot deployment
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APA (6th Edition):
Notomista, G. (2020). Long-duration robot autonomy: From control algorithms to robot design. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63700
Chicago Manual of Style (16th Edition):
Notomista, Gennaro. “Long-duration robot autonomy: From control algorithms to robot design.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/63700.
MLA Handbook (7th Edition):
Notomista, Gennaro. “Long-duration robot autonomy: From control algorithms to robot design.” 2020. Web. 27 Feb 2021.
Vancouver:
Notomista G. Long-duration robot autonomy: From control algorithms to robot design. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/63700.
Council of Science Editors:
Notomista G. Long-duration robot autonomy: From control algorithms to robot design. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63700
Georgia Tech
10.
Young, Carol C.
Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms.
Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech
URL: http://hdl.handle.net/1853/64012
► This thesis models online ensemble learning algorithms to obtain theoretical analyses of various performance metrics. Online ensemble learning algorithms often serve to learn unknown, possibly…
(more)
▼ This thesis models online ensemble learning algorithms to obtain theoretical analyses of various performance metrics. Online ensemble learning algorithms often serve to learn unknown, possibly time-varying, probability distributions or interact with other learning systems. Their simplicity allows flexibility in design choices, leading to variations that balance adaptiveness and consistency and allows for chatter resistant co-learning. To analyze online ensemble learning algorithms for these variations this work provides a method for the creation of automata by properly selecting states. These automata provide an analytical framework to quantify the adaptiveness and consistency of online ensemble learning algorithms when interacting with a probability distribution. The resulting Markov chain provides quantatative metrics of adaptiveness and consistency can be calculated through mathematical formulas, other than relying on numerical simulations. This analysis shows that the Multi Expert Algorithm (MEA) achieves a higher consistency than the more adaptive Weighted Majority Algorithm (WMA), and a higher adaptiveness than the more consistent Winnow algorithm, thus achieving a balance between the historical algorithms in terms of the adaptiveness and consistency metrics. The automata also provides an analytical framework to identify chatter which can happen when an online learning algorithm is used by a robot to predict human intention when interacting with a human. When chatter happens, the learning algorithm continually changes its prediction, without reaching a constant prediction of human intention. Utilizing Rescorla-Wagner model for human learning, we analyze an expert based online learning algorithm and identify if chatter will occur, and if so what conditions will cause chatter.
Advisors/Committee Members: Zhang, Fumin (advisor), Howard, Ayanna (committee member), Chernova, Sonia (committee member), Coogan, Samuel (committee member), Wang, Yue (committee member).
Subjects/Keywords: Machine Learning; Markov chain; Learning algorithms
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APA (6th Edition):
Young, C. C. (2019). Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64012
Chicago Manual of Style (16th Edition):
Young, Carol C. “Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms.” 2019. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/64012.
MLA Handbook (7th Edition):
Young, Carol C. “Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms.” 2019. Web. 27 Feb 2021.
Vancouver:
Young CC. Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/64012.
Council of Science Editors:
Young CC. Quantitative Analysis of Adaptiveness and Consistency of a Class of Online Learning Algorithms. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/64012
Georgia Tech
11.
Yang, Xuejiao.
Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques.
Degree: PhD, Chemical and Biomolecular Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/64107
► In applications such as wind energy, industrial robotics, and chemical processing, increases in complexity and automation have made component malfunctions and other abnormal events (i.e.,…
(more)
▼ In applications such as wind energy, industrial robotics, and chemical processing, increases in complexity and automation have made component malfunctions and other abnormal events (i.e., faults) an ever-present threat to safety and reliability. Thus, fault detection algorithms have become an essential feature of modern control systems, leading to significant decreases in downtime, maintenance costs, and catastrophic failures. However, while well-established statistical methods are effective in many cases, they often fail to make the critical distinction between faults and normal process disturbances. An attractive alternative is to exploit detailed process models that, at least in principle, can be used to characterize the outputs consistent with normal operation, providing a rigorous basis for fault detection. Methods that furnish a guaranteed enclosure of these outputs (e.g., using set-based state estimators) are particularly attractive because they eliminate the possibility of costly false alarms and provide better trade-offs between false alarms and missed faults. However, such methods are currently impractical for systems with strong nonlinearities or large uncertainties. For such systems, existing set-based estimation techniques often produce enclosures that are far too conservative to be useful for fault detection, or avoid this only at excessive computational cost. Thus, there is a critical need for advanced algorithms that can rapidly detect faults for realistic nonlinear systems, and do so rigorously in the presence of disturbances, measurement noise, and large model uncertainties.
In this thesis, we develop an advanced set-based state estimation method for uncertain nonlinear systems, and demonstrate its application to provide fast and accurate fault detection for such systems. Our proposed estimation method is performed recursively in two steps. First, the prediction step computes an enclosure of the possible model outputs under uncertainty over one discrete time step. Next, the correction step uses the process measurements to update this enclosure by eliminating regions that are not consistent with the measurements. In contrast to existing set-based estimation methods, our prediction step makes use of our previously developed continuous-time differential inequalities (DI) method and extends it to discrete-time systems. The DI method uses very efficient interval computations, but is effective at mitigating some key sources of conservatism typically associated with such computations in discrete-time systems by exploiting redundant model equations, which can be easily found in many representative reaction and separation models. Moreover, we make use of past process measurements in a novel way in the prediction step, potentially leading to further improvements in bound accuracy. Our results demonstrate that, for a variety of systems of practical interest, the proposed prediction step in the state estimation algorithm leads to dramatically tighter enclosures of the states, with only modest additional…
Advisors/Committee Members: Scott, Joseph K. (advisor), Grover, Martha A. (committee member), Styczynski, Mark P. (committee member), Realff, Matthew J. (committee member), Coogan, Samuel (committee member).
Subjects/Keywords: Set-based fault detection; reachability analysis; set-based state estimation
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APA ·
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MLA ·
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CSE |
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APA (6th Edition):
Yang, X. (2020). Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64107
Chicago Manual of Style (16th Edition):
Yang, Xuejiao. “Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/64107.
MLA Handbook (7th Edition):
Yang, Xuejiao. “Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques.” 2020. Web. 27 Feb 2021.
Vancouver:
Yang X. Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/64107.
Council of Science Editors:
Yang X. Rapid and Accurate Fault Detection for Uncertain Nonlinear Systems Using Advanced Set-Based State Estimation Techniques. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64107
Georgia Tech
12.
Srinivasan, Mohit.
Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution.
Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech
URL: http://hdl.handle.net/1853/64132
► Safety critical control applications are ubiquitous, and hence synthesizing control algorithms with formal guarantees on safety and task satisfaction is of great importance. Tasks such…
(more)
▼ Safety critical control applications are ubiquitous, and hence synthesizing control algorithms with formal guarantees on safety and task satisfaction is of great importance. Tasks such as motion planning in unknown environments or planning for autonomous vehicles require controllers that satisfy a sequence of operations. In addition, the system must execute trajectories which are dynamically feasible, safe, and respect actuator constraints. In this thesis, a barrier certificate-based approach to synthesize controllers for safe robotic task execution is detailed. Control barrier functions have recently emerged as a tool to guarantee safety and reachability for dynamical systems, and they can be conveniently encoded in computationally efficient quadratic programs, making them amenable to real-time implementation. Leveraging these useful features, a framework for translating a given user defined specification to a sequence of barrier certificate-based controllers is introduced. The specification is formalized using linear temporal logic, a tool from formal methods literature. Executing such a sequence of controllers results in satisfaction of the given specification. Implementation results on a multi-robot test bed are provided. Furthermore, in order to guarantee task satisfaction, it is important to address certain assumptions that are prevalent in barrier functions-based literature such as feasibility of the quadratic programs, negligence of system volume when guaranteeing safety, and knowledge of the safe sets in unknown operating environments. We thus provide techniques to address the above assumptions and discuss simulation and experimental results to demonstrate the efficiency of the proposed approaches.
Advisors/Committee Members: Coogan, Samuel (advisor), Egerstedt, Magnus (committee member), Vela, Patricio (committee member), Di Cairano, Stefano (committee member), Zhao, Ye (committee member).
Subjects/Keywords: Control barrier functions; Safety; Robotics; Quadratic programs; Control theory; Autonomous systems
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Export
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APA (6th Edition):
Srinivasan, M. (2020). Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64132
Chicago Manual of Style (16th Edition):
Srinivasan, Mohit. “Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution.” 2020. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/64132.
MLA Handbook (7th Edition):
Srinivasan, Mohit. “Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution.” 2020. Web. 27 Feb 2021.
Vancouver:
Srinivasan M. Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/64132.
Council of Science Editors:
Srinivasan M. Synthesis of Barrier Certificate-Based Controllers for Safe Robotic Task Execution. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64132
13.
Olsen, Mark Ryan.
Power-aware hybrid-dynamical approach to coverage control in multi-robot systems.
Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech
URL: http://hdl.handle.net/1853/59940
► This thesis develops an algorithm which allows robots in a multi-robot team to optimize for battery power while performing coverage control so as to maximize…
(more)
▼ This thesis develops an algorithm which allows robots in a multi-robot team to optimize for battery power while performing coverage control so as to maximize the mission life of the multi-robot team. We envision a scenario where robots with limited battery supply are executing the well known Lloyd's algorithm in order to effectively cover a certain region. We perform a trade-off between the distance of a robot from the centroid of its Voronoi cell, and the energy required to traverse that distance. In order to execute this trade-off two different strategies are presented – in one case, the reduction in cost due to coverage is compared against the energy required to traverse the distance to the centroid, and using a user-defined threshold, the decision is made. Then, a more sophisticated algorithm is used to perform the trade-off where the robots solves a switch-time optimization problem to decide whether it should move or it should stay.
Advisors/Committee Members: Egerstedt, Magnus (advisor), Coogan, Samuel (committee member), Wardi, Yorai (committee member).
Subjects/Keywords: Power; Robotics; Multi-robot; Coverage; Controls
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APA (6th Edition):
Olsen, M. R. (2018). Power-aware hybrid-dynamical approach to coverage control in multi-robot systems. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59940
Chicago Manual of Style (16th Edition):
Olsen, Mark Ryan. “Power-aware hybrid-dynamical approach to coverage control in multi-robot systems.” 2018. Masters Thesis, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/59940.
MLA Handbook (7th Edition):
Olsen, Mark Ryan. “Power-aware hybrid-dynamical approach to coverage control in multi-robot systems.” 2018. Web. 27 Feb 2021.
Vancouver:
Olsen MR. Power-aware hybrid-dynamical approach to coverage control in multi-robot systems. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/59940.
Council of Science Editors:
Olsen MR. Power-aware hybrid-dynamical approach to coverage control in multi-robot systems. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59940
14.
Almubarak, Hassan A.
Infinite horizon nonlinear quadratic cost regulator.
Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech
URL: http://hdl.handle.net/1853/60821
► Infinite horizon optimal control has been a leading methodology for both linear and nonlinear systems. The Hamilton-Jacobi-Bellman (HJB) approach is a very effective approach for…
(more)
▼ Infinite horizon optimal control has been a leading methodology for both linear and nonlinear systems. The Hamilton-Jacobi-Bellman (HJB) approach is a very effective approach
for infinite horizon optimal control which involves solving the associated nonlinear partial differential equation known as the HJB equation. Because of the importance and high difficulty of solving the HJB equation, different techniques and approximations to
solve the HJB equation are proposed in the literature. In the case of linear systems, the HJB equation becomes the known Reccati equation which provides the well known and
powerful Linear Quadratic Regulator (LQR). Therefore, the focus of this research is to generalize the idea of the LQR and develop a Nonlinear Quadratic cost Regulator (NLQR) based on the solution of the HJB equation for the infinite horizon problem. We present a novel and an efficient technique based on
Taylor series expansion for the HJB equation around an equilibrium point. Utilizing a set of minimal polynomial basis functions that includes all possible combinations of the states,
a nonlinear matrix equation similar to the Riccati equation is constructed from the HJB equation. Solving this nonlinear matrix equation term by term renders the associated value
function (i.e, optimal cost-to-go) and the optimal controller with a prescribed truncation order. The computational complexity of this approach is shown to have only a polynomial growth rate with respect to the series order. The developed HJB based equation can be solved independently of the current states
and hence the optimal nonlinear control can be obtained a-priori offline for smooth nonlinear control affine systems. A general recursive closed form procedure to find the coefficients
of high order control laws is provided. Set of examples are presented with different systems natures and nonlinearities including inputs saturation.
Advisors/Committee Members: Sadegh, Nader (advisor), Taylor, David G. (advisor), Coogan, Samuel (committee member), Vela, Patricio (committee member).
Subjects/Keywords: Nonlinear control; Optimal control; Hamilton-Jacobi-Bellman; Infinite horizon; Feedback control
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APA (6th Edition):
Almubarak, H. A. (2018). Infinite horizon nonlinear quadratic cost regulator. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60821
Chicago Manual of Style (16th Edition):
Almubarak, Hassan A. “Infinite horizon nonlinear quadratic cost regulator.” 2018. Masters Thesis, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/60821.
MLA Handbook (7th Edition):
Almubarak, Hassan A. “Infinite horizon nonlinear quadratic cost regulator.” 2018. Web. 27 Feb 2021.
Vancouver:
Almubarak HA. Infinite horizon nonlinear quadratic cost regulator. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/60821.
Council of Science Editors:
Almubarak HA. Infinite horizon nonlinear quadratic cost regulator. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60821
15.
Glotfelter, Paul.
Specification composition and controller synthesis for robotic systems.
Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech
URL: http://hdl.handle.net/1853/61238
► From precision agriculture to autonomous-transportation systems, robotic systems have been proposed to accomplish a number of tasks. However, these systems typically require satisfaction of multiple…
(more)
▼ From precision agriculture to autonomous-transportation systems, robotic systems have been proposed to accomplish a number of tasks. However, these systems typically require satisfaction of multiple constraints, such as safety or connectivity maintenance, while completing their primary objectives. The objective of this thesis is to endow robotic systems with a Boolean-composition and controller-synthesis framework for specifications of objectives and constraints. Barrier functions represent one method to enforce such constraints via forward set invariance, and Lyapunov functions offer a similar guarantee for set stability. This thesis focuses on building a system of Boolean logic for barrier and Lyapunov functions by using min and max operators. As these objects inherently introduce nonsmoothness, this thesis extends the theory on barrier functions to nonsmooth barrier functions and, subsequently, to controlled systems via control nonsmooth barrier functions. However, synthesizing controllers with respect to a nonsmooth function may create discontinuities; as such, this thesis develops a controller-synthesis framework that, despite creating discontinuities, still produces valid controllers (i.e., ones that satisfy the objectives and constraints). These developments have been successfully applied to a variety of robotic systems, including remotely accessible testbeds, autonomous-transportation scenarios, and leader-follower systems.
Advisors/Committee Members: Egerstedt, Magnus (advisor), Cortes, Jorge (committee member), Rogers, Jonathan (committee member), Hutchinson, Seth (committee member), Coogan, Samuel (committee member).
Subjects/Keywords: Boolean composition; Nonsmooth analysis; Differential inclusions; Multi-robot systems; Robotic systems; Collision avoidance; Leader follower
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APA ·
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APA (6th Edition):
Glotfelter, P. (2019). Specification composition and controller synthesis for robotic systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61238
Chicago Manual of Style (16th Edition):
Glotfelter, Paul. “Specification composition and controller synthesis for robotic systems.” 2019. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021.
http://hdl.handle.net/1853/61238.
MLA Handbook (7th Edition):
Glotfelter, Paul. “Specification composition and controller synthesis for robotic systems.” 2019. Web. 27 Feb 2021.
Vancouver:
Glotfelter P. Specification composition and controller synthesis for robotic systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1853/61238.
Council of Science Editors:
Glotfelter P. Specification composition and controller synthesis for robotic systems. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61238
. 
Open Access Theses and Dissertations
