Safe Navigation of Networked Robots Under Localization Uncertainty Using Robust Control Barrier Functions

Abstract

5G networks have the potential to provide external sensor data and offload computations for future industrial mobile robots. To enable these benefits while maintaining safety, we propose a modular architecture, including an onboard safety filter for the velocity control loop. The safety filter leverages robust control barrier functions to guarantee safety from collisions under bounded localization uncertainty. Initial experiments are performed to quantify the localization uncertainty and generate suitable bounds for the safety filter. We then derive the safety filter, and analyze its conservatism numerically. Finally, the method is demonstrated in experiments using an ABB Mobile YuMi® Research Platform robot.