Multi-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control
Abstract
The problem of dynamic locomotion over rough terrain requires both accurate foot placement together with an emphasis on dynamic stability. Existing approaches to this problem prioritize immediate safe foot placement over longer term dynamic stability considerations, or relegate the coordination of foot placement and dynamic stability to heuristic methods. We propose a multi-layered locomotion framework that unifies Control Barrier Functions (CBFs) with Model Predictive Control (MPC) to simultaneously achieve safe foot placement and dynamic stability. Our approach incorporates CBF based safety constraints both in a low frequency kinodynamic MPC formulation and a high frequency inverse dynamics tracking controller. This ensures that safety-critical execution is considered when optimizing locomotion over a longer horizon. We validate the proposed method in a 3D stepping-stone scenario in simulation and experimentally on the ANYmal quadruped platform.
Additional Information
© 2021 IEEE. R. Grandia and M. Hutter are supported via the European Union's Horizon 2020 research and innovation programme under grant agreement No 780883 and by the Swiss National Science Foundation (SNSF) as part of project No. 188596. A. Taylor, and A. Ames are supported via DARPA award HR00111890035, and NSF awards 1923239 and 1924526.Attached Files
Accepted Version - 2011.00032.pdf
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Additional details
- Eprint ID
- 106554
- Resolver ID
- CaltechAUTHORS:20201109-140942301
- European Research Council (ERC)
- 780883
- Swiss National Science Foundation (SNSF)
- 188596
- Defense Advanced Research Projects Agency (DARPA)
- HR00111890035
- NSF
- CMMI-1923239
- NSF
- ECCS-1924526
- Created
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2020-11-09Created from EPrint's datestamp field
- Updated
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2021-12-20Created from EPrint's last_modified field