Guaranteed obstacle avoidance for multi-robot operations with limited actuation: a control barrier function approach
- Creators
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Chen, Yuxiao
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Singletary, Andrew
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Ames, Aaron D.
Abstract
This letter considers the problem of obstacle avoidance for multiple robotic agents moving in an environment with obstacles. A decentralized supervisory controller is synthesized based on control barrier functions (CBF) that guarantees obstacle avoidance with limited actuation capability. The proposed method is applicable to general nonlinear robot dynamics and is scalable to an arbitrary number of agents. Agent-to-agent communication is not required, yet a simple broadcasting scheme improves the performance of the algorithm. The key idea is based on a control barrier function constructed with a backup controller, and we show that by assuming other agents respecting the same CBF condition, the supervisory control algorithm can be implemented decentrally and guarantees obstacle avoidance for all agents.
Additional Information
© 2020 IEEE. Manuscript received March 16, 2020; revised May 13, 2020; accepted June 1, 2020. Date of publication June 9, 2020; date of current version June 22, 2020. The work of Yuxiao Chen was supported by SRI/AFOSR under Award FA8750-19-C-0089. The work of Andrew Singletary was supported by DARPA under Award NNN12AA01C. The work of Aaron D. Ames was supported by NSF CPS under Award 1932091. Recommended by Senior Editor F. Dabbene.Additional details
- Eprint ID
- 103867
- DOI
- 10.1109/lcsys.2020.3000748
- Resolver ID
- CaltechAUTHORS:20200612-105359901
- FA8750-19-C-0089
- Air Force Office of Scientific Research (AFOSR)
- NNN12AA01C
- NASA
- Defense Advanced Research Projects Agency (DARPA)
- CNS-1932091
- NSF
- Created
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2020-06-12Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field