Distributed game-theoretic trajectory planning for multi-agent interactions
Williams, Zachary James
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https://hdl.handle.net/2142/121564
Description
Title
Distributed game-theoretic trajectory planning for multi-agent interactions
Author(s)
Williams, Zachary James
Issue Date
2023-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Mehr, Negar Z
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Dynamic Game Theory
Multi-agent Navigation
Potential Games
Path Planning For Multiple Robots
Multi-robot Systems
Interactive Trajectory Planning
Language
eng
Abstract
In this work, we develop a scalable, local trajectory optimization algorithm that enables robots to interact with other agents. It has been shown that the interactions of multiple agents can be successfully captured in game-theoretic formulations, where the interaction outcome can be best modeled via the equilibria of the underlying dynamic game. However, it is challenging to compute equilibria of dynamic games as it involves simultaneously solving a set of coupled optimal control problems. Existing solvers operate in a centralized fashion and do not scale up tractably to multiple interacting agents. We enable scalable distributed game-theoretic planning by leveraging the structure inherent in multi-agent interactions, namely, interactions belonging to the class of dynamic potential games. Since equilibria of dynamic potential games can be found by minimizing a single potential function, we can apply distributed and decentralized control techniques to seek equilibria of multi-agent interactions in a scalable and distributed manner. We compare the performance of our algorithm with a centralized interactive planner in a number of simulation studies and demonstrate that our algorithm results in better efficiency and scalability. We further evaluate our method in hardware experiments involving multiple quadcopters.
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