*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Title: Safety Embedded Optimal Decision Making and Control via Barrier States
Committee:
Dr. Theodorou, Advisor
Dr. Sadegh, Co-Advisor
Dr. Coogan, Chair
Dr. Vamvoudakis
Dr. Vela
Abstract: The objective of the proposed research is to confront the trade-off between safety restrictions and performance through designing the appropriate mathematical tools used to develop provably safe and robust optimal control and planning for general safety-critical dynamical systems and path constraints. In this thesis, aiming to develop algorithms that achieve safety and optimality simultaneously, I first pursue the design of embedded barrier states (BaS) as a means of integrating safety into performance objectives. BaS are subsequently used with various optimal control frameworks, such as nonlinear quadratic regulators (NLQR), differential dynamic programming (DDP) and model predictive control (MPC) to develop novel algorithms that produce safety-aware and robust decision making. Additionally, the proposed algorithms are considered for uncertain safety critical problems in which game theoretic and stochastic formulations are utilized. This proposal suggests studying the employment of barrier states methods in different safety-critical application such as multi-agent systems, data-driven representations, and perception. Furthermore, I propose to apply the aforementioned safety-embedded methodology to Lyapunov analyses as well as constrained dynamical optimization. The proposed work and algorithms are to be deployed on real-world systems.
