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You searched for +publisher:"Georgia Tech" +contributor:("Theodorou, Evangelos A."). Showing records 1 – 9 of 9 total matches.

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Georgia Tech

1. Williams, Grady Robert. Model predictive path integral control: Theoretical foundations and applications to autonomous driving.

Degree: PhD, Computer Science, 2019, Georgia Tech

 This thesis presents a new approach for stochastic model predictive (optimal) control: model predictive path integral control, which is based on massive parallel sampling of… (more)

Subjects/Keywords: Stochastic optimal control; Autonomous driving

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APA (6th Edition):

Williams, G. R. (2019). Model predictive path integral control: Theoretical foundations and applications to autonomous driving. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62666

Chicago Manual of Style (16th Edition):

Williams, Grady Robert. “Model predictive path integral control: Theoretical foundations and applications to autonomous driving.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/62666.

MLA Handbook (7th Edition):

Williams, Grady Robert. “Model predictive path integral control: Theoretical foundations and applications to autonomous driving.” 2019. Web. 05 Mar 2021.

Vancouver:

Williams GR. Model predictive path integral control: Theoretical foundations and applications to autonomous driving. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/62666.

Council of Science Editors:

Williams GR. Model predictive path integral control: Theoretical foundations and applications to autonomous driving. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62666


Georgia Tech

2. Cheng, Ching An. Efficient and principled robot learning: Theory and algorithms.

Degree: PhD, Interactive Computing, 2020, Georgia Tech

 Roboticists have long envisioned fully-automated robots that can operate reliably in unstructured environments. This is an exciting but extremely difficult problem; in order to succeed,… (more)

Subjects/Keywords: Online learning; Control theory; Robotics; Optimization; Reinforcement learning; Imitation learning

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APA (6th Edition):

Cheng, C. A. (2020). Efficient and principled robot learning: Theory and algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62733

Chicago Manual of Style (16th Edition):

Cheng, Ching An. “Efficient and principled robot learning: Theory and algorithms.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/62733.

MLA Handbook (7th Edition):

Cheng, Ching An. “Efficient and principled robot learning: Theory and algorithms.” 2020. Web. 05 Mar 2021.

Vancouver:

Cheng CA. Efficient and principled robot learning: Theory and algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/62733.

Council of Science Editors:

Cheng CA. Efficient and principled robot learning: Theory and algorithms. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62733


Georgia Tech

3. Exarchos, Ioannis. Stochastic optimal control - a forward and backward sampling approach.

Degree: PhD, Aerospace Engineering, 2017, Georgia Tech

 Stochastic optimal control has seen significant recent development, motivated by its success in a plethora of engineering applications, such as autonomous systems, robotics, neuroscience, and… (more)

Subjects/Keywords: Stochastic optimal control; Forward and backward stochastic differential equations

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APA (6th Edition):

Exarchos, I. (2017). Stochastic optimal control - a forward and backward sampling approach. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59263

Chicago Manual of Style (16th Edition):

Exarchos, Ioannis. “Stochastic optimal control - a forward and backward sampling approach.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/59263.

MLA Handbook (7th Edition):

Exarchos, Ioannis. “Stochastic optimal control - a forward and backward sampling approach.” 2017. Web. 05 Mar 2021.

Vancouver:

Exarchos I. Stochastic optimal control - a forward and backward sampling approach. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/59263.

Council of Science Editors:

Exarchos I. Stochastic optimal control - a forward and backward sampling approach. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59263


Georgia Tech

4. Zafar, Munzir. Whole body control of wheeled inverted pendulum humanoids.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 A framework for controlling a Wheeled Inverted Pendulum (WIP) Humanoid to perform useful interactions with the environment, while dynamically balancing itself on two wheels, was… (more)

Subjects/Keywords: Whole body control; Wheeled inverted pendulum; Humanoids; Hierarchical; Optimization; Operational space; Model predictive control

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APA (6th Edition):

Zafar, M. (2019). Whole body control of wheeled inverted pendulum humanoids. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61739

Chicago Manual of Style (16th Edition):

Zafar, Munzir. “Whole body control of wheeled inverted pendulum humanoids.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/61739.

MLA Handbook (7th Edition):

Zafar, Munzir. “Whole body control of wheeled inverted pendulum humanoids.” 2019. Web. 05 Mar 2021.

Vancouver:

Zafar M. Whole body control of wheeled inverted pendulum humanoids. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/61739.

Council of Science Editors:

Zafar M. Whole body control of wheeled inverted pendulum humanoids. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61739


Georgia Tech

5. Drews, Paul Michael. Visual attention for high speed driving.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Coupling of control and perception is an especially difficult problem. This thesis investigates this problem in the context of aggressive off-road driving. By jointly developing… (more)

Subjects/Keywords: Robotics; Computer vision; Autonomous vehicles; Neural networks; High speed

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APA (6th Edition):

Drews, P. M. (2018). Visual attention for high speed driving. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61183

Chicago Manual of Style (16th Edition):

Drews, Paul Michael. “Visual attention for high speed driving.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/61183.

MLA Handbook (7th Edition):

Drews, Paul Michael. “Visual attention for high speed driving.” 2018. Web. 05 Mar 2021.

Vancouver:

Drews PM. Visual attention for high speed driving. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/61183.

Council of Science Editors:

Drews PM. Visual attention for high speed driving. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61183


Georgia Tech

6. Goldfain, Brian. Autonomous Rally Racing with AutoRally and Model Predictive Control.

Degree: PhD, Interactive Computing, 2019, Georgia Tech

 The ability to conduct experiments in the real world is a critical step for roboticists working to create autonomous systems that achieve human-level task performance.… (more)

Subjects/Keywords: autonomous racing; cost function optimization; self-driving vehicle

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APA (6th Edition):

Goldfain, B. (2019). Autonomous Rally Racing with AutoRally and Model Predictive Control. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63529

Chicago Manual of Style (16th Edition):

Goldfain, Brian. “Autonomous Rally Racing with AutoRally and Model Predictive Control.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/63529.

MLA Handbook (7th Edition):

Goldfain, Brian. “Autonomous Rally Racing with AutoRally and Model Predictive Control.” 2019. Web. 05 Mar 2021.

Vancouver:

Goldfain B. Autonomous Rally Racing with AutoRally and Model Predictive Control. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/63529.

Council of Science Editors:

Goldfain B. Autonomous Rally Racing with AutoRally and Model Predictive Control. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/63529

7. Pan, Yunpeng. Learning control via probabilistic trajectory optimization.

Degree: PhD, Aerospace Engineering, 2017, Georgia Tech

 A central problem in the field of robotics is to develop real-time planning and control algorithms for autonomous systems to behave intelligently under uncertainty. While… (more)

Subjects/Keywords: Optimal control; Robotics; Artificial intelligence; Machine learning

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APA (6th Edition):

Pan, Y. (2017). Learning control via probabilistic trajectory optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59278

Chicago Manual of Style (16th Edition):

Pan, Yunpeng. “Learning control via probabilistic trajectory optimization.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/59278.

MLA Handbook (7th Edition):

Pan, Yunpeng. “Learning control via probabilistic trajectory optimization.” 2017. Web. 05 Mar 2021.

Vancouver:

Pan Y. Learning control via probabilistic trajectory optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/59278.

Council of Science Editors:

Pan Y. Learning control via probabilistic trajectory optimization. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59278

8. Sun, Wei. Pursuit-evasion and differential games under uncertainties.

Degree: PhD, Aerospace Engineering, 2017, Georgia Tech

 Differential games involves multi-person decision making under conflicts in the context of dynamical systems. It has found its application on a large range of areas,… (more)

Subjects/Keywords: Optimal control; Differential game; Pursuit-evasion; Multiplayer; Flow field; Differential dynamic programming; Stochastic system

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APA (6th Edition):

Sun, W. (2017). Pursuit-evasion and differential games under uncertainties. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58664

Chicago Manual of Style (16th Edition):

Sun, Wei. “Pursuit-evasion and differential games under uncertainties.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/58664.

MLA Handbook (7th Edition):

Sun, Wei. “Pursuit-evasion and differential games under uncertainties.” 2017. Web. 05 Mar 2021.

Vancouver:

Sun W. Pursuit-evasion and differential games under uncertainties. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/58664.

Council of Science Editors:

Sun W. Pursuit-evasion and differential games under uncertainties. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58664

9. Bakshi, Kaivalya Sanjeev. Large scale stochastic control: Algorithms, optimality and stability.

Degree: PhD, Aerospace Engineering, 2018, Georgia Tech

 Optimal control of large-scale multi-agent networked systems which describe social networks, macro-economies, traffic and robot swarms is a topic of interest in engineering, biophysics and… (more)

Subjects/Keywords: Nonlinear control; Robust control; Optimal control; Mean field games; Large scale systems

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APA (6th Edition):

Bakshi, K. S. (2018). Large scale stochastic control: Algorithms, optimality and stability. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61179

Chicago Manual of Style (16th Edition):

Bakshi, Kaivalya Sanjeev. “Large scale stochastic control: Algorithms, optimality and stability.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 05, 2021. http://hdl.handle.net/1853/61179.

MLA Handbook (7th Edition):

Bakshi, Kaivalya Sanjeev. “Large scale stochastic control: Algorithms, optimality and stability.” 2018. Web. 05 Mar 2021.

Vancouver:

Bakshi KS. Large scale stochastic control: Algorithms, optimality and stability. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/1853/61179.

Council of Science Editors:

Bakshi KS. Large scale stochastic control: Algorithms, optimality and stability. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61179

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