Title
Contingency Games for Multi-Agent Interaction
Author
Peters, L. (TU Delft Learning & Autonomous Control) 
Bajcsy, Andrea (Carnegie Mellon University)
Chiu, Chih Yuan (University of California Berkeley)
Fridovich-Keil, David (The University of Texas at Austin)
Laine, Forrest (VanderBilt University)
Ferranti, L. (TU Delft Learning & Autonomous Control)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control)
Date
2024
Abstract
Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under uncertainty. In this work we take a game-theoretic perspective on contingency planning, tailored to multi-agent scenarios in which a robot's actions impact the decisions of other agents and vice versa. The resulting contingency game allows the robot to efficiently interact with other agents by generating strategic motion plans conditioned on multiple possible intents for other actors in the scene. Contingency games are parameterized via a scalar variable which represents a future time when intent uncertainty will be resolved. By estimating this parameter online, we construct a game-theoretic motion planner that adapts to changing beliefs while anticipating future certainty. We show that existing variants of game-theoretic planning under uncertainty are readily obtained as special cases of contingency games. Through a series of simulated autonomous driving scenarios, we demonstrate that contingency games close the gap between certainty-equivalent games that commit to a single hypothesis and non-contingent multi-hypothesis games that do not account for future uncertainty reduction.
Subject
Contingency management
Games
Human-Aware Motion Planning
Motion and Path Planning
Pedestrians
Planning
Planning under Uncertainty
Robots
Trajectory
Uncertainty
To reference this document use:
http://resolver.tudelft.nl/uuid:259ae4f1-f642-43cc-854f-5c99dd237315
DOI
https://doi.org/10.1109/LRA.2024.3354548
Embargo date
2024-07-16
ISSN
2377-3766
Source
IEEE Robotics and Automation Letters, 9 (3), 2208-2215
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2024 L. Peters, Andrea Bajcsy, Chih Yuan Chiu, David Fridovich-Keil, Forrest Laine, L. Ferranti, J. Alonso-Mora