Model-Free Safety-Critical Control for Robotic Systems
Tamás G. Molnár, Ryan K. Cosner, Andrew W. Singletary, Wyatt Ubellacker, Aaron D. Ames
Abstract
This letter presents a framework for the safety-critical control of robotic systems, when safety is defined on safe regions in the configuration space. To maintain safety, we synthesize a safe velocity based on control barrier function theory without relying on a – potentially complicated – high-fidelity dynamical model of the robot. Then, we track the safe velocity with a tracking controller. This culminates in <i>model-free safety critical control</i>. We prove theoretical safety guarantees for the proposed method. Finally, we demonstrate that this approach is application-agnostic. We execute an obstacle avoidance task with a Segway in high-fidelity simulation, as well as with a Drone and a Quadruped in hardware experiments.
BibTeX
@inproceedings{ral2022_modelfreesafetyc,
title = {Model-Free Safety-Critical Control for Robotic Systems},
author = {Tamás G. Molnár and Ryan K. Cosner and Andrew W. Singletary and Wyatt Ubellacker and Aaron D. Ames},
booktitle = {RA-L 2022},
year = {2022}
}