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Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties

Cheng, Richard and Khojasteh, Mohammad Javad and Ames, Aaron D. and Burdick, Joel W. (2020) Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties. In: 2020 59th IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 777-783. ISBN 978-1-7281-7447-1. https://resolver.caltech.edu/CaltechAUTHORS:20200527-075148688

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Abstract

Robots operating in real world settings must navigate and maintain safety while interacting with many heterogeneous agents and obstacles. Multi-Agent Control Barrier Functions (CBF) have emerged as a computationally efficient tool to guarantee safety in multi-agent environments, but they assume perfect knowledge of both the robot dynamics and other agents' dynamics. While knowledge of the robot's dynamics might be reasonably well known, the heterogeneity of agents in real-world environments means there will always be considerable uncertainty in our prediction of other agents' dynamics. This work aims to learn high-confidence bounds for these dynamic uncertainties using Matrix-Variate Gaussian Process models, and incorporates them into a robust multi-agent CBF framework. We transform the resulting min-max robust CBF into a quadratic program, which can be efficiently solved in real time. We verify via simulation results that the nominal multi-agent CBF is often violated during agent interactions, whereas our robust formulation maintains safety with a much higher probability and adapts to learned uncertainties.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CDC42340.2020.9304395DOIArticle
https://arxiv.org/abs/2004.05273arXivDiscussion Paper
ORCID:
AuthorORCID
Cheng, Richard0000-0001-8301-9169
Khojasteh, Mohammad Javad0000-0002-8459-6483
Ames, Aaron D.0000-0003-0848-3177
Additional Information:© 2020 IEEE.
Record Number:CaltechAUTHORS:20200527-075148688
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200527-075148688
Official Citation:R. Cheng, M. J. Khojasteh, A. D. Ames and J. W. Burdick, "Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties," 2020 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), 2020, pp. 777-783, doi: 10.1109/CDC42340.2020.9304395
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103484
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:27 May 2020 15:54
Last Modified:22 Jan 2021 21:32

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