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You searched for subject:(Modeling Control AND Learning for Soft Robots). Showing records 1 – 30 of 1128 total matches.

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Georgia Tech

1. 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

 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 (6th 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 (16th Edition):

Wang, Sen. “Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model.” 2020. Masters Thesis, Georgia Tech. Accessed April 15, 2021. http://hdl.handle.net/1853/64143.

MLA Handbook (7th Edition):

Wang, Sen. “Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model.” 2020. Web. 15 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 15]. 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


Colorado State University

2. Pawlowski, Ben. Modeling, simulation, and control of soft robots.

Degree: MS(M.S.), Mechanical Engineering, 2019, Colorado State University

Soft robots are a new type of robot with deformable bodies and muscle-like actuations, which are fundamentally different from traditional robots with rigid links and… (more)

Subjects/Keywords: reinforcement learning; symplectic integration; soft robots; model predictive control

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APA (6th Edition):

Pawlowski, B. (2019). Modeling, simulation, and control of soft robots. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/199791

Chicago Manual of Style (16th Edition):

Pawlowski, Ben. “Modeling, simulation, and control of soft robots.” 2019. Masters Thesis, Colorado State University. Accessed April 15, 2021. http://hdl.handle.net/10217/199791.

MLA Handbook (7th Edition):

Pawlowski, Ben. “Modeling, simulation, and control of soft robots.” 2019. Web. 15 Apr 2021.

Vancouver:

Pawlowski B. Modeling, simulation, and control of soft robots. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10217/199791.

Council of Science Editors:

Pawlowski B. Modeling, simulation, and control of soft robots. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/199791

3. Kennedy, Monroe David. Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation.

Degree: 2019, University of Pennsylvania

 As advances are made in robotic hardware, the complexity of tasks they are capable of performing also increases. One goal of modern robotics is to… (more)

Subjects/Keywords: Manipulation Planning; Model Learning for Control; Motion Control; Service Robots; Mechanical Engineering; Robotics

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APA (6th Edition):

Kennedy, M. D. (2019). Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/3299

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

Chicago Manual of Style (16th Edition):

Kennedy, Monroe David. “Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation.” 2019. Thesis, University of Pennsylvania. Accessed April 15, 2021. https://repository.upenn.edu/edissertations/3299.

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

MLA Handbook (7th Edition):

Kennedy, Monroe David. “Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation.” 2019. Web. 15 Apr 2021.

Vancouver:

Kennedy MD. Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation. [Internet] [Thesis]. University of Pennsylvania; 2019. [cited 2021 Apr 15]. Available from: https://repository.upenn.edu/edissertations/3299.

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

Council of Science Editors:

Kennedy MD. Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation. [Thesis]. University of Pennsylvania; 2019. Available from: https://repository.upenn.edu/edissertations/3299

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


University of Illinois – Urbana-Champaign

4. Havens, Aaron. Model-based approaches for learning control from multi-modal data.

Degree: MS, Aerospace Engineering, 2020, University of Illinois – Urbana-Champaign

 Methods like deep reinforcement learning (DRL) have gained increasing attention when solving very general continuous control tasks in a model-free end-to-end fashion. However, there has… (more)

Subjects/Keywords: model predictive control; reinforcement learning; soft robotics

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APA (6th Edition):

Havens, A. (2020). Model-based approaches for learning control from multi-modal data. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/108550

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

Chicago Manual of Style (16th Edition):

Havens, Aaron. “Model-based approaches for learning control from multi-modal data.” 2020. Thesis, University of Illinois – Urbana-Champaign. Accessed April 15, 2021. http://hdl.handle.net/2142/108550.

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

MLA Handbook (7th Edition):

Havens, Aaron. “Model-based approaches for learning control from multi-modal data.” 2020. Web. 15 Apr 2021.

Vancouver:

Havens A. Model-based approaches for learning control from multi-modal data. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2020. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/2142/108550.

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

Council of Science Editors:

Havens A. Model-based approaches for learning control from multi-modal data. [Thesis]. University of Illinois – Urbana-Champaign; 2020. Available from: http://hdl.handle.net/2142/108550

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

5. Nguyen, Tuan. Learning Control of Closed-Kinematic Chain Mechanism Manipulators.

Degree: 2020, The Catholic University of America

Human beings possess the ability to learn from experience from their repeated activities. For example, professional athletes exercise repeatedly to acquire an ideal form of… (more)

Subjects/Keywords: CKCM Manipulators; Iterative Learning Control; Learning control; Parallel robots; Robot Manipulators

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APA (6th Edition):

Nguyen, T. (2020). Learning Control of Closed-Kinematic Chain Mechanism Manipulators. (Thesis). The Catholic University of America. Retrieved from http://hdl.handle.net/1961/cuislandora:214714

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

Chicago Manual of Style (16th Edition):

Nguyen, Tuan. “Learning Control of Closed-Kinematic Chain Mechanism Manipulators.” 2020. Thesis, The Catholic University of America. Accessed April 15, 2021. http://hdl.handle.net/1961/cuislandora:214714.

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

MLA Handbook (7th Edition):

Nguyen, Tuan. “Learning Control of Closed-Kinematic Chain Mechanism Manipulators.” 2020. Web. 15 Apr 2021.

Vancouver:

Nguyen T. Learning Control of Closed-Kinematic Chain Mechanism Manipulators. [Internet] [Thesis]. The Catholic University of America; 2020. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/1961/cuislandora:214714.

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

Council of Science Editors:

Nguyen T. Learning Control of Closed-Kinematic Chain Mechanism Manipulators. [Thesis]. The Catholic University of America; 2020. Available from: http://hdl.handle.net/1961/cuislandora:214714

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


Hong Kong University of Science and Technology

6. Li, Siyi CSE. Learning perception and control for robot intelligence.

Degree: 2019, Hong Kong University of Science and Technology

 Autonomous robots that can assist humans in the daily unstructured world have been a long standing vision of robotics and artificial intelligence (AI). Such autonomous… (more)

Subjects/Keywords: Autonomous robots ; Mathematical models ; Robots ; Control systems ; Machine learning ; Artificial intelligence ; Perception

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APA (6th Edition):

Li, S. C. (2019). Learning perception and control for robot intelligence. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-100352 ; https://doi.org/10.14711/thesis-991012730762103412 ; http://repository.ust.hk/ir/bitstream/1783.1-100352/1/th_redirect.html

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

Chicago Manual of Style (16th Edition):

Li, Siyi CSE. “Learning perception and control for robot intelligence.” 2019. Thesis, Hong Kong University of Science and Technology. Accessed April 15, 2021. http://repository.ust.hk/ir/Record/1783.1-100352 ; https://doi.org/10.14711/thesis-991012730762103412 ; http://repository.ust.hk/ir/bitstream/1783.1-100352/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Li, Siyi CSE. “Learning perception and control for robot intelligence.” 2019. Web. 15 Apr 2021.

Vancouver:

Li SC. Learning perception and control for robot intelligence. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2019. [cited 2021 Apr 15]. Available from: http://repository.ust.hk/ir/Record/1783.1-100352 ; https://doi.org/10.14711/thesis-991012730762103412 ; http://repository.ust.hk/ir/bitstream/1783.1-100352/1/th_redirect.html.

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

Council of Science Editors:

Li SC. Learning perception and control for robot intelligence. [Thesis]. Hong Kong University of Science and Technology; 2019. Available from: http://repository.ust.hk/ir/Record/1783.1-100352 ; https://doi.org/10.14711/thesis-991012730762103412 ; http://repository.ust.hk/ir/bitstream/1783.1-100352/1/th_redirect.html

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

7. XU WENJUN. MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES.

Degree: 2015, National University of Singapore

Subjects/Keywords: flexible surgical manipulator; data-driven methods; reinforcement learning; learn from demonstration; learning control; soft robots

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APA (6th Edition):

WENJUN, X. (2015). MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/152768

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

Chicago Manual of Style (16th Edition):

WENJUN, XU. “MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES.” 2015. Thesis, National University of Singapore. Accessed April 15, 2021. http://scholarbank.nus.edu.sg/handle/10635/152768.

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

MLA Handbook (7th Edition):

WENJUN, XU. “MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES.” 2015. Web. 15 Apr 2021.

Vancouver:

WENJUN X. MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES. [Internet] [Thesis]. National University of Singapore; 2015. [cited 2021 Apr 15]. Available from: http://scholarbank.nus.edu.sg/handle/10635/152768.

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

Council of Science Editors:

WENJUN X. MODELING AND TASK AUTOMATION FOR FLEXIBLE SURGICAL MANIPULATORS VIA DATA-DRIVEN APPROACHES. [Thesis]. National University of Singapore; 2015. Available from: http://scholarbank.nus.edu.sg/handle/10635/152768

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


University of Waterloo

8. Tsang, Florence. Learning a Motion Policy to Navigate Environments with Structured Uncertainty.

Degree: 2020, University of Waterloo

 Navigating in uncertain environments is a fundamental ability that robots must have in many applications such as moving goods in a warehouse or transporting materials… (more)

Subjects/Keywords: robot navigation; reinforcement learning; motion planning; Robots – Motion; Uncertainty (Information theory); Robots – Programming; Robots – Control systems.

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APA (6th Edition):

Tsang, F. (2020). Learning a Motion Policy to Navigate Environments with Structured Uncertainty. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15562

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

Chicago Manual of Style (16th Edition):

Tsang, Florence. “Learning a Motion Policy to Navigate Environments with Structured Uncertainty.” 2020. Thesis, University of Waterloo. Accessed April 15, 2021. http://hdl.handle.net/10012/15562.

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

MLA Handbook (7th Edition):

Tsang, Florence. “Learning a Motion Policy to Navigate Environments with Structured Uncertainty.” 2020. Web. 15 Apr 2021.

Vancouver:

Tsang F. Learning a Motion Policy to Navigate Environments with Structured Uncertainty. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10012/15562.

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

Council of Science Editors:

Tsang F. Learning a Motion Policy to Navigate Environments with Structured Uncertainty. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15562

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

9. Geisert, Mathieu. Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens.

Degree: Docteur es, Robotique, 2018, Toulouse, INSA

Quelle sont les points communs entre un robot humanoïde et un quadrimoteur ? Et bien, pas grand-chose… Cette thèse est donc dédiée au développement d’algorithmes… (more)

Subjects/Keywords: Contrôle optimal numérique; Contrôle hiérarchique; Apprentissage automatique; Planification de contacts; Robots humanoïdes; Robots aériens; Numerical optimal control; Machine learning; Machine learning; Contact planning; Humanoid robots; Aerial robots; 629.8

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APA (6th Edition):

Geisert, M. (2018). Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens. (Doctoral Dissertation). Toulouse, INSA. Retrieved from http://www.theses.fr/2018ISAT0011

Chicago Manual of Style (16th Edition):

Geisert, Mathieu. “Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens.” 2018. Doctoral Dissertation, Toulouse, INSA. Accessed April 15, 2021. http://www.theses.fr/2018ISAT0011.

MLA Handbook (7th Edition):

Geisert, Mathieu. “Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens.” 2018. Web. 15 Apr 2021.

Vancouver:

Geisert M. Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens. [Internet] [Doctoral dissertation]. Toulouse, INSA; 2018. [cited 2021 Apr 15]. Available from: http://www.theses.fr/2018ISAT0011.

Council of Science Editors:

Geisert M. Optimal control and machine learning for humanoid and aerial robots : Contrôle optimal et apprentissage automatique pour robots humanoïdes et aériens. [Doctoral Dissertation]. Toulouse, INSA; 2018. Available from: http://www.theses.fr/2018ISAT0011


Delft University of Technology

10. van Lohuijzen, Michiel (author). Towards incremental kinesthetic teaching of bipedal walking.

Degree: 2017, Delft University of Technology

 The large dimensionality of walking motions is a challenge for robot learning. The human seems designated to assist in this learning process, because of their… (more)

Subjects/Keywords: Kinesthetic Teaching; Iterative Learning Control; Bipedal Walking; Learning from Demonstrations; Learning by Imitation; Robots

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APA (6th Edition):

van Lohuijzen, M. (. (2017). Towards incremental kinesthetic teaching of bipedal walking. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:08c3139b-bd0b-40f5-93c2-877e1b14b24a

Chicago Manual of Style (16th Edition):

van Lohuijzen, Michiel (author). “Towards incremental kinesthetic teaching of bipedal walking.” 2017. Masters Thesis, Delft University of Technology. Accessed April 15, 2021. http://resolver.tudelft.nl/uuid:08c3139b-bd0b-40f5-93c2-877e1b14b24a.

MLA Handbook (7th Edition):

van Lohuijzen, Michiel (author). “Towards incremental kinesthetic teaching of bipedal walking.” 2017. Web. 15 Apr 2021.

Vancouver:

van Lohuijzen M(. Towards incremental kinesthetic teaching of bipedal walking. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 15]. Available from: http://resolver.tudelft.nl/uuid:08c3139b-bd0b-40f5-93c2-877e1b14b24a.

Council of Science Editors:

van Lohuijzen M(. Towards incremental kinesthetic teaching of bipedal walking. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:08c3139b-bd0b-40f5-93c2-877e1b14b24a


University of Plymouth

11. Loviken, Pontus. Fast online model learning for controlling complex real-world robots.

Degree: PhD, 2019, University of Plymouth

 How can real robots with many degrees of freedom - without previous knowledge of themselves or their environment - act and use the resulting observations… (more)

Subjects/Keywords: model learning; Reinforcement learning; Online learning; Goal babbling; inverse models; Micro data learning; Developmental robotics; real-world robots; sensorimotor control

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

APA (6th Edition):

Loviken, P. (2019). Fast online model learning for controlling complex real-world robots. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/15078

Chicago Manual of Style (16th Edition):

Loviken, Pontus. “Fast online model learning for controlling complex real-world robots.” 2019. Doctoral Dissertation, University of Plymouth. Accessed April 15, 2021. http://hdl.handle.net/10026.1/15078.

MLA Handbook (7th Edition):

Loviken, Pontus. “Fast online model learning for controlling complex real-world robots.” 2019. Web. 15 Apr 2021.

Vancouver:

Loviken P. Fast online model learning for controlling complex real-world robots. [Internet] [Doctoral dissertation]. University of Plymouth; 2019. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10026.1/15078.

Council of Science Editors:

Loviken P. Fast online model learning for controlling complex real-world robots. [Doctoral Dissertation]. University of Plymouth; 2019. Available from: http://hdl.handle.net/10026.1/15078


University of Illinois – Chicago

12. Monfort, Mathew. Methods in Large Scale Inverse Optimal Control.

Degree: 2016, University of Illinois – Chicago

 As our technology continues to evolve, so does the complexity of the problems that we expect our systems to solve. The challenge is that these… (more)

Subjects/Keywords: machine learning; artificial intelligence; inverse optimal control; graph search; autonomous agents; reinforcement learning; path distributions; robotic control; robotics; robots; activity recognition

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APA (6th Edition):

Monfort, M. (2016). Methods in Large Scale Inverse Optimal Control. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21540

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

Chicago Manual of Style (16th Edition):

Monfort, Mathew. “Methods in Large Scale Inverse Optimal Control.” 2016. Thesis, University of Illinois – Chicago. Accessed April 15, 2021. http://hdl.handle.net/10027/21540.

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

MLA Handbook (7th Edition):

Monfort, Mathew. “Methods in Large Scale Inverse Optimal Control.” 2016. Web. 15 Apr 2021.

Vancouver:

Monfort M. Methods in Large Scale Inverse Optimal Control. [Internet] [Thesis]. University of Illinois – Chicago; 2016. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10027/21540.

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

Council of Science Editors:

Monfort M. Methods in Large Scale Inverse Optimal Control. [Thesis]. University of Illinois – Chicago; 2016. Available from: http://hdl.handle.net/10027/21540

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


Universitat Politècnica de València

13. Solanes Galbis, Juan Ernesto. MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL .

Degree: 2015, Universitat Politècnica de València

 [EN] This thesis deals with two characteristic problems in visual feedback robot control: 1) sensor latency; 2) providing suitable trajectories for the robot and for… (more)

Subjects/Keywords: Visual feedback control; visual servoing; multi-rate control; nonlinear control; industrial robot systems; wheeled robots; machine learning.

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APA (6th Edition):

Solanes Galbis, J. E. (2015). MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/57951

Chicago Manual of Style (16th Edition):

Solanes Galbis, Juan Ernesto. “MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL .” 2015. Doctoral Dissertation, Universitat Politècnica de València. Accessed April 15, 2021. http://hdl.handle.net/10251/57951.

MLA Handbook (7th Edition):

Solanes Galbis, Juan Ernesto. “MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL .” 2015. Web. 15 Apr 2021.

Vancouver:

Solanes Galbis JE. MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2015. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10251/57951.

Council of Science Editors:

Solanes Galbis JE. MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL . [Doctoral Dissertation]. Universitat Politècnica de València; 2015. Available from: http://hdl.handle.net/10251/57951

14. Provost, Jefferson, 1968-. Reinforcement learning in high-diameter, continuous environments.

Degree: PhD, Computer Sciences, 2007, University of Texas – Austin

 Many important real-world robotic tasks have high diameter, that is, their solution requires a large number of primitive actions by the robot. For example, they… (more)

Subjects/Keywords: Robots – Control systems; Machine learning

learning, and a set of continuous perceptual features for continuous control. 3. Learn High-level… …control and causal levels of SSH provide a framework for grounding the reinforcement learning… …to distant locations using primitive motor control commands. In addition, modern robots are… …environment. Reinforcement learning (RL) has shown promise as a method for automatic… …actions, that using these new actions dramatically speeds up learning for high-diameter… 

Page 1 Page 2 Page 3 Page 4 Page 5

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APA (6th Edition):

Provost, Jefferson, 1. (2007). Reinforcement learning in high-diameter, continuous environments. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3263

Chicago Manual of Style (16th Edition):

Provost, Jefferson, 1968-. “Reinforcement learning in high-diameter, continuous environments.” 2007. Doctoral Dissertation, University of Texas – Austin. Accessed April 15, 2021. http://hdl.handle.net/2152/3263.

MLA Handbook (7th Edition):

Provost, Jefferson, 1968-. “Reinforcement learning in high-diameter, continuous environments.” 2007. Web. 15 Apr 2021.

Vancouver:

Provost, Jefferson 1. Reinforcement learning in high-diameter, continuous environments. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2007. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/2152/3263.

Council of Science Editors:

Provost, Jefferson 1. Reinforcement learning in high-diameter, continuous environments. [Doctoral Dissertation]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3263


Louisiana State University

15. Ma, Yan. Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.

Degree: PhD, Chemical Engineering, 2020, Louisiana State University

  This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses… (more)

Subjects/Keywords: process control; optimization; machine learning; reinforcement learning; process modeling

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APA (6th Edition):

Ma, Y. (2020). Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. (Doctoral Dissertation). Louisiana State University. Retrieved from https://digitalcommons.lsu.edu/gradschool_dissertations/5427

Chicago Manual of Style (16th Edition):

Ma, Yan. “Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.” 2020. Doctoral Dissertation, Louisiana State University. Accessed April 15, 2021. https://digitalcommons.lsu.edu/gradschool_dissertations/5427.

MLA Handbook (7th Edition):

Ma, Yan. “Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.” 2020. Web. 15 Apr 2021.

Vancouver:

Ma Y. Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. [Internet] [Doctoral dissertation]. Louisiana State University; 2020. [cited 2021 Apr 15]. Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/5427.

Council of Science Editors:

Ma Y. Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. [Doctoral Dissertation]. Louisiana State University; 2020. Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/5427


Texas State University – San Marcos

16. Huff, Shelby A. TIG Welding Skill Extraction using a Machine Learning Algorithm.

Degree: MS, Manufacturing Engineering, 2017, Texas State University – San Marcos

 Tungsten Inert Gas (TIG) welding is the superior arc welding process used in the manufacturing industry for high quality welds. Skilled welders are capable of… (more)

Subjects/Keywords: TIG Welding; Artificial Inteligence; Machine Learning; Gaussian Process Regression; Industrial Robots; Manufacturing Engineering; Manufacturing processes; Light metals – Welding; Robots – Control systems; Machine learning; Computer algorithms

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APA (6th Edition):

Huff, S. A. (2017). TIG Welding Skill Extraction using a Machine Learning Algorithm. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6930

Chicago Manual of Style (16th Edition):

Huff, Shelby A. “TIG Welding Skill Extraction using a Machine Learning Algorithm.” 2017. Masters Thesis, Texas State University – San Marcos. Accessed April 15, 2021. https://digital.library.txstate.edu/handle/10877/6930.

MLA Handbook (7th Edition):

Huff, Shelby A. “TIG Welding Skill Extraction using a Machine Learning Algorithm.” 2017. Web. 15 Apr 2021.

Vancouver:

Huff SA. TIG Welding Skill Extraction using a Machine Learning Algorithm. [Internet] [Masters thesis]. Texas State University – San Marcos; 2017. [cited 2021 Apr 15]. Available from: https://digital.library.txstate.edu/handle/10877/6930.

Council of Science Editors:

Huff SA. TIG Welding Skill Extraction using a Machine Learning Algorithm. [Masters Thesis]. Texas State University – San Marcos; 2017. Available from: https://digital.library.txstate.edu/handle/10877/6930


University of Windsor

17. Mellatshahi, Seyed Navid. Learning Control of Robotic Arm Using Deep Q-Neural Network.

Degree: MS, Electrical and Computer Engineering, 2021, University of Windsor

 Enabling robotic systems for autonomous actions such as driverless systems, is a very complex task in real-world scenarios due to uncertainties. Machine learning capabilities have… (more)

Subjects/Keywords: AI in Robotic; Artificial Intelligence in Industrial Robots; Deep Reinforcement Learning; DQN; Inverted Pendulum; Learning Control

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APA (6th Edition):

Mellatshahi, S. N. (2021). Learning Control of Robotic Arm Using Deep Q-Neural Network. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/8568

Chicago Manual of Style (16th Edition):

Mellatshahi, Seyed Navid. “Learning Control of Robotic Arm Using Deep Q-Neural Network.” 2021. Masters Thesis, University of Windsor. Accessed April 15, 2021. https://scholar.uwindsor.ca/etd/8568.

MLA Handbook (7th Edition):

Mellatshahi, Seyed Navid. “Learning Control of Robotic Arm Using Deep Q-Neural Network.” 2021. Web. 15 Apr 2021.

Vancouver:

Mellatshahi SN. Learning Control of Robotic Arm Using Deep Q-Neural Network. [Internet] [Masters thesis]. University of Windsor; 2021. [cited 2021 Apr 15]. Available from: https://scholar.uwindsor.ca/etd/8568.

Council of Science Editors:

Mellatshahi SN. Learning Control of Robotic Arm Using Deep Q-Neural Network. [Masters Thesis]. University of Windsor; 2021. Available from: https://scholar.uwindsor.ca/etd/8568

18. Wang, Ting. Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics.

Degree: Docteur es, Traitement du Signal et des Images, 2012, Université Paris-Est

 L'objectif de cette thèse s'inscrit dans la cadre général du développement d'une stratégie de contrôle intelligent distribué en robotique collective. En effet, dans un avenir… (more)

Subjects/Keywords: Stratégie de contrôle intelligent; Robotique collective; Formation de robots; Apprentissage artificiel; Application logistique; Intelligent Distributed Control Strategies; Collective Robotics; Robots' formation; Machine learning; Logistic application

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

APA (6th Edition):

Wang, T. (2012). Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2012PEST1109

Chicago Manual of Style (16th Edition):

Wang, Ting. “Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics.” 2012. Doctoral Dissertation, Université Paris-Est. Accessed April 15, 2021. http://www.theses.fr/2012PEST1109.

MLA Handbook (7th Edition):

Wang, Ting. “Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics.” 2012. Web. 15 Apr 2021.

Vancouver:

Wang T. Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics. [Internet] [Doctoral dissertation]. Université Paris-Est; 2012. [cited 2021 Apr 15]. Available from: http://www.theses.fr/2012PEST1109.

Council of Science Editors:

Wang T. Contribution à l’étude, la conception et la mise en oeuvre de stratégie de contrôle intelligent distribué en robotique collective : Contribution to study, dand implementation of intelligent distributed control strategies for collective robotics. [Doctoral Dissertation]. Université Paris-Est; 2012. Available from: http://www.theses.fr/2012PEST1109


Georgia Tech

19. Powers, Matthew D. Applying inter-layer conflict resolution to hybrid robot control architectures.

Degree: PhD, Computing, 2010, Georgia Tech

 In this document, we propose and examine the novel use of a learning mechanism between the reactive and deliberative layers of a hybrid robot control(more)

Subjects/Keywords: Robotics; Planning; Machine learning; Architecture; Robots Control systems; Mobile robots

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APA (6th Edition):

Powers, M. D. (2010). Applying inter-layer conflict resolution to hybrid robot control architectures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33979

Chicago Manual of Style (16th Edition):

Powers, Matthew D. “Applying inter-layer conflict resolution to hybrid robot control architectures.” 2010. Doctoral Dissertation, Georgia Tech. Accessed April 15, 2021. http://hdl.handle.net/1853/33979.

MLA Handbook (7th Edition):

Powers, Matthew D. “Applying inter-layer conflict resolution to hybrid robot control architectures.” 2010. Web. 15 Apr 2021.

Vancouver:

Powers MD. Applying inter-layer conflict resolution to hybrid robot control architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/1853/33979.

Council of Science Editors:

Powers MD. Applying inter-layer conflict resolution to hybrid robot control architectures. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/33979


Loughborough University

20. Zhao, Yuchen. Human skill capturing and modelling using wearable devices.

Degree: PhD, 2017, Loughborough University

 Industrial robots are delivering more and more manipulation services in manufacturing. However, when the task is complex, it is difficult to programme a robot to… (more)

Subjects/Keywords: 670.42; Manufacturing automation; Force based control; Motion Capturing (MoCap); Learning from Demonstration (LfD); Surface electromyography (sEMG); Robots

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APA (6th Edition):

Zhao, Y. (2017). Human skill capturing and modelling using wearable devices. (Doctoral Dissertation). Loughborough University. Retrieved from http://hdl.handle.net/2134/27613

Chicago Manual of Style (16th Edition):

Zhao, Yuchen. “Human skill capturing and modelling using wearable devices.” 2017. Doctoral Dissertation, Loughborough University. Accessed April 15, 2021. http://hdl.handle.net/2134/27613.

MLA Handbook (7th Edition):

Zhao, Yuchen. “Human skill capturing and modelling using wearable devices.” 2017. Web. 15 Apr 2021.

Vancouver:

Zhao Y. Human skill capturing and modelling using wearable devices. [Internet] [Doctoral dissertation]. Loughborough University; 2017. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/2134/27613.

Council of Science Editors:

Zhao Y. Human skill capturing and modelling using wearable devices. [Doctoral Dissertation]. Loughborough University; 2017. Available from: http://hdl.handle.net/2134/27613


Michigan State University

21. Howden, Sally Jean. Towards a learning system for robot hand-eye coordination.

Degree: PhD, Department of Computer Science, 1996, Michigan State University

Subjects/Keywords: Machine learning; Robots – Control systems; Eye-hand coordination

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APA (6th Edition):

Howden, S. J. (1996). Towards a learning system for robot hand-eye coordination. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:29763

Chicago Manual of Style (16th Edition):

Howden, Sally Jean. “Towards a learning system for robot hand-eye coordination.” 1996. Doctoral Dissertation, Michigan State University. Accessed April 15, 2021. http://etd.lib.msu.edu/islandora/object/etd:29763.

MLA Handbook (7th Edition):

Howden, Sally Jean. “Towards a learning system for robot hand-eye coordination.” 1996. Web. 15 Apr 2021.

Vancouver:

Howden SJ. Towards a learning system for robot hand-eye coordination. [Internet] [Doctoral dissertation]. Michigan State University; 1996. [cited 2021 Apr 15]. Available from: http://etd.lib.msu.edu/islandora/object/etd:29763.

Council of Science Editors:

Howden SJ. Towards a learning system for robot hand-eye coordination. [Doctoral Dissertation]. Michigan State University; 1996. Available from: http://etd.lib.msu.edu/islandora/object/etd:29763


University of New Mexico

22. Appel, Titus. The development of a robotic test bed with applications in Q-learning.

Degree: Electrical and Computer Engineering, 2012, University of New Mexico

 In this work, we show the design, development, and testing of an autonomous ground vehicle for experiments in learning and intelligent transportation research. We then… (more)

Subjects/Keywords: Autonomous robots – Design and construction; Reinforcement learning; Feedback control systems; Intelligent transportation systems – Design and construction.

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APA (6th Edition):

Appel, T. (2012). The development of a robotic test bed with applications in Q-learning. (Masters Thesis). University of New Mexico. Retrieved from http://hdl.handle.net/1928/17331

Chicago Manual of Style (16th Edition):

Appel, Titus. “The development of a robotic test bed with applications in Q-learning.” 2012. Masters Thesis, University of New Mexico. Accessed April 15, 2021. http://hdl.handle.net/1928/17331.

MLA Handbook (7th Edition):

Appel, Titus. “The development of a robotic test bed with applications in Q-learning.” 2012. Web. 15 Apr 2021.

Vancouver:

Appel T. The development of a robotic test bed with applications in Q-learning. [Internet] [Masters thesis]. University of New Mexico; 2012. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/1928/17331.

Council of Science Editors:

Appel T. The development of a robotic test bed with applications in Q-learning. [Masters Thesis]. University of New Mexico; 2012. Available from: http://hdl.handle.net/1928/17331

23. Khodayi-mehr, Reza. MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS .

Degree: 2019, Duke University

  Mathematical models that describe different processes and phenomena are of paramount importance in many robotics applications. Nevertheless, utilization of high-fidelity models, particularly Partial Differential… (more)

Subjects/Keywords: Robotics; Computer science; Statistics; Active Sensing; Advection-Diffusion PDE; Learning and Control; Mobile Robots; Neural Networks; Source Identification

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APA (6th Edition):

Khodayi-mehr, R. (2019). MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/18683

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

Chicago Manual of Style (16th Edition):

Khodayi-mehr, Reza. “MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS .” 2019. Thesis, Duke University. Accessed April 15, 2021. http://hdl.handle.net/10161/18683.

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

MLA Handbook (7th Edition):

Khodayi-mehr, Reza. “MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS .” 2019. Web. 15 Apr 2021.

Vancouver:

Khodayi-mehr R. MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS . [Internet] [Thesis]. Duke University; 2019. [cited 2021 Apr 15]. Available from: http://hdl.handle.net/10161/18683.

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

Council of Science Editors:

Khodayi-mehr R. MODEL-BASED LEARNING AND CONTROL OF ADVECTION-DIFFUSION TRANSPORT USING MOBILE ROBOTS . [Thesis]. Duke University; 2019. Available from: http://hdl.handle.net/10161/18683

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


University of Notre Dame

24. Na Yu. Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>.

Degree: Aerospace and Mechanical Engineering, 2016, University of Notre Dame

  Current research has shown that building energy consumption contributes to more than 40% of the total energy use in United States. In recent years,… (more)

Subjects/Keywords: Building energy modeling; model-based predictive control; decision-tree learning

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APA (6th Edition):

Yu, N. (2016). Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/p8418k7434s

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

Chicago Manual of Style (16th Edition):

Yu, Na. “Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>.” 2016. Thesis, University of Notre Dame. Accessed April 15, 2021. https://curate.nd.edu/show/p8418k7434s.

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

MLA Handbook (7th Edition):

Yu, Na. “Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>.” 2016. Web. 15 Apr 2021.

Vancouver:

Yu N. Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>. [Internet] [Thesis]. University of Notre Dame; 2016. [cited 2021 Apr 15]. Available from: https://curate.nd.edu/show/p8418k7434s.

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

Council of Science Editors:

Yu N. Model-Based Design Optimization and Predictive Control to Minimize Energy Consumption of a Building</h1>. [Thesis]. University of Notre Dame; 2016. Available from: https://curate.nd.edu/show/p8418k7434s

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


UCLA

25. Lakshmipathy, Arjun Sriram. Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control.

Degree: Computer Science, 2018, UCLA

 This thesis presents a novel, biomimetic model of the eye for realistic virtual human anima- tion. We also introduce a deep learning approach to oculomotor… (more)

Subjects/Keywords: Computer science; Biomechanical human animation; Biomimetic Vision; Deep learning; Eye modeling; Oculomotor Control; Sensorimotor Control

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APA (6th Edition):

Lakshmipathy, A. S. (2018). Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/4770b06c

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

Chicago Manual of Style (16th Edition):

Lakshmipathy, Arjun Sriram. “Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control.” 2018. Thesis, UCLA. Accessed April 15, 2021. http://www.escholarship.org/uc/item/4770b06c.

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

MLA Handbook (7th Edition):

Lakshmipathy, Arjun Sriram. “Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control.” 2018. Web. 15 Apr 2021.

Vancouver:

Lakshmipathy AS. Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control. [Internet] [Thesis]. UCLA; 2018. [cited 2021 Apr 15]. Available from: http://www.escholarship.org/uc/item/4770b06c.

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

Council of Science Editors:

Lakshmipathy AS. Biomimetic Modeling of the Eye and Deep Neuromuscular Oculomotor Control. [Thesis]. UCLA; 2018. Available from: http://www.escholarship.org/uc/item/4770b06c

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


Carnegie Mellon University

26. Silver, David. Learning Preference Models for Autonomous Mobile Robots in Complex Domains.

Degree: 2010, Carnegie Mellon University

 Achieving robust and reliable autonomous operation even in complex unstructured environments is a central goal of field robotics. As the environments and scenarios to which… (more)

Subjects/Keywords: Mobile Robots; Field Robotics; Learning from Demonstration; Imitation Learning; Inverse Optimal Control; Active Learning; Preference Models; Cost Functions; Parameter Tuning; Artificial Intelligence and Robotics

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APA (6th Edition):

Silver, D. (2010). Learning Preference Models for Autonomous Mobile Robots in Complex Domains. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/551

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

Chicago Manual of Style (16th Edition):

Silver, David. “Learning Preference Models for Autonomous Mobile Robots in Complex Domains.” 2010. Thesis, Carnegie Mellon University. Accessed April 15, 2021. http://repository.cmu.edu/dissertations/551.

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

MLA Handbook (7th Edition):

Silver, David. “Learning Preference Models for Autonomous Mobile Robots in Complex Domains.” 2010. Web. 15 Apr 2021.

Vancouver:

Silver D. Learning Preference Models for Autonomous Mobile Robots in Complex Domains. [Internet] [Thesis]. Carnegie Mellon University; 2010. [cited 2021 Apr 15]. Available from: http://repository.cmu.edu/dissertations/551.

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

Council of Science Editors:

Silver D. Learning Preference Models for Autonomous Mobile Robots in Complex Domains. [Thesis]. Carnegie Mellon University; 2010. Available from: http://repository.cmu.edu/dissertations/551

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


Delft University of Technology

27. Koryakovskiy, I. Safer reinforcement learning for robotics.

Degree: 2018, Delft University of Technology

 Reinforcement learning is an active research area in the fields of artificial intelligence and machine learning, with applications in control. The most important feature of… (more)

Subjects/Keywords: Reinforcement Learning; Humanoid Robots; Optimal Control; Learning and Adaptive Systems; Nonlinear Model Predictive Control; Parametric Uncertainties; Structural Uncertainties; Bipedal Robots

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APA (6th Edition):

Koryakovskiy, I. (2018). Safer reinforcement learning for robotics. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; 7923c257-e81f-4e29-adf7-bd6014d9da6a ; 10.4233/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:isbn:978-5-00058-959-5 ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a

Chicago Manual of Style (16th Edition):

Koryakovskiy, I. “Safer reinforcement learning for robotics.” 2018. Doctoral Dissertation, Delft University of Technology. Accessed April 15, 2021. http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; 7923c257-e81f-4e29-adf7-bd6014d9da6a ; 10.4233/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:isbn:978-5-00058-959-5 ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a.

MLA Handbook (7th Edition):

Koryakovskiy, I. “Safer reinforcement learning for robotics.” 2018. Web. 15 Apr 2021.

Vancouver:

Koryakovskiy I. Safer reinforcement learning for robotics. [Internet] [Doctoral dissertation]. Delft University of Technology; 2018. [cited 2021 Apr 15]. Available from: http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; 7923c257-e81f-4e29-adf7-bd6014d9da6a ; 10.4233/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:isbn:978-5-00058-959-5 ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a.

Council of Science Editors:

Koryakovskiy I. Safer reinforcement learning for robotics. [Doctoral Dissertation]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; 7923c257-e81f-4e29-adf7-bd6014d9da6a ; 10.4233/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; urn:isbn:978-5-00058-959-5 ; urn:NBN:nl:ui:24-uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a ; http://resolver.tudelft.nl/uuid:7923c257-e81f-4e29-adf7-bd6014d9da6a


University of Notre Dame

28. Arash Rahnama. Learning-Based Approaches to Control, Estimation and Modeling</h1>.

Degree: Electrical Engineering, 2018, University of Notre Dame

  Design of cyber-physical systems requires control approaches that provide stability, performance, compositionality, robustness and security. QSR-Dissipativite and passive dynamical systems exhibit stability and robustness… (more)

Subjects/Keywords: Learning-based control; Systems and Control; Multi-Agent Systems; Networked Systems; Machine Learning; Estimation, Modeling and Prediction; Cyber-Physical Systems

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APA (6th Edition):

Rahnama, A. (2018). Learning-Based Approaches to Control, Estimation and Modeling</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/bk128913b51

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

Chicago Manual of Style (16th Edition):

Rahnama, Arash. “Learning-Based Approaches to Control, Estimation and Modeling</h1>.” 2018. Thesis, University of Notre Dame. Accessed April 15, 2021. https://curate.nd.edu/show/bk128913b51.

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

MLA Handbook (7th Edition):

Rahnama, Arash. “Learning-Based Approaches to Control, Estimation and Modeling</h1>.” 2018. Web. 15 Apr 2021.

Vancouver:

Rahnama A. Learning-Based Approaches to Control, Estimation and Modeling</h1>. [Internet] [Thesis]. University of Notre Dame; 2018. [cited 2021 Apr 15]. Available from: https://curate.nd.edu/show/bk128913b51.

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

Council of Science Editors:

Rahnama A. Learning-Based Approaches to Control, Estimation and Modeling</h1>. [Thesis]. University of Notre Dame; 2018. Available from: https://curate.nd.edu/show/bk128913b51

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


UCLA

29. Teng, Kuo-Tai. Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control.

Degree: Mechanical Engineering, 2014, UCLA

 This thesis develops learning control algorithms for power converters and precisionmotion control. The repetitive control is designed for power converters to providezero steady state error… (more)

Subjects/Keywords: Mechanical engineering; Iterative Learning Control; Noncircular Machining; PWM Inverter; PWM Rectifier; Repetitive Control; Repetitive Control for Multi-input Multi-output system

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

APA (6th Edition):

Teng, K. (2014). Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/91c52795

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

Chicago Manual of Style (16th Edition):

Teng, Kuo-Tai. “Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control.” 2014. Thesis, UCLA. Accessed April 15, 2021. http://www.escholarship.org/uc/item/91c52795.

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

MLA Handbook (7th Edition):

Teng, Kuo-Tai. “Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control.” 2014. Web. 15 Apr 2021.

Vancouver:

Teng K. Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control. [Internet] [Thesis]. UCLA; 2014. [cited 2021 Apr 15]. Available from: http://www.escholarship.org/uc/item/91c52795.

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

Council of Science Editors:

Teng K. Repetitive and Iterative Learning Control for Power Converter and Precision Motion Control. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/91c52795

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

30. Melnyk, Artem. Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach.

Degree: Docteur es, STIC (sciences et technologies de l'information et de la communication) - Cergy, 2014, Cergy-Pontoise; Donecʹkij nacíonalʹnij uníversitet (Ukraine)

Les robots intégrés aux chaînes de production sont généralement isolés des ouvriers et ne prévoient pas d'interaction physique avec les humains. Dans le futur, le… (more)

Subjects/Keywords: Commande bio-Inspirée; Reseaux des neurones; Interaction physique; Robotique humanoide; Automatique; Apprentissage; Bio-Inspired control; Neural networks; Physical interaction; Humanoid robots; Control; Learning

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

APA (6th Edition):

Melnyk, A. (2014). Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach. (Doctoral Dissertation). Cergy-Pontoise; Donecʹkij nacíonalʹnij uníversitet (Ukraine). Retrieved from http://www.theses.fr/2014CERG0745

Chicago Manual of Style (16th Edition):

Melnyk, Artem. “Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach.” 2014. Doctoral Dissertation, Cergy-Pontoise; Donecʹkij nacíonalʹnij uníversitet (Ukraine). Accessed April 15, 2021. http://www.theses.fr/2014CERG0745.

MLA Handbook (7th Edition):

Melnyk, Artem. “Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach.” 2014. Web. 15 Apr 2021.

Vancouver:

Melnyk A. Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach. [Internet] [Doctoral dissertation]. Cergy-Pontoise; Donecʹkij nacíonalʹnij uníversitet (Ukraine); 2014. [cited 2021 Apr 15]. Available from: http://www.theses.fr/2014CERG0745.

Council of Science Editors:

Melnyk A. Perfectionnement des algorithmes de contrôle-commande des robots manipulateur électriques en interaction physique avec leur environnement par une approche bio-inspirée : Improvement of control algorithms of electrical robot arms in physical interaction with their environment with bio-inspired approach. [Doctoral Dissertation]. Cergy-Pontoise; Donecʹkij nacíonalʹnij uníversitet (Ukraine); 2014. Available from: http://www.theses.fr/2014CERG0745

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