Robust Barrier Functions for a Fully Autonomous, Remotely Accessible Swarm-Robotics Testbed

TL;DR

This paper introduces robust barrier functions for control-affine systems, enabling the Robotarium swarm-robotics testbed to operate fully autonomously despite disturbances, ensuring safety constraints are maintained automatically and minimally invasively.

Contribution

The paper develops a robust barrier function framework for disturbed control systems, enhancing autonomous safety constraint satisfaction in the Robotarium testbed.

Findings

Robust barrier functions effectively handle unmodeled disturbances.

Experimental validation shows autonomous operation over long periods.

System maintains safety constraints with minimal intervention.

Abstract

The Robotarium, a remotely accessible swarm-robotics testbed, has provided free, open access to robotics and controls research for hundreds of users in thousands of experiments. This high level of usage requires autonomy in the system, which mainly corresponds to constraint satisfaction in the context of users' submissions. In other words, in case that the users' inputs to the robots may lead to collisions, these inputs must be altered to avoid these collisions automatically. However, these alterations must be minimal so as to preserve the users' objective in the experiment. Toward this end, the system has utilized barrier functions, which admit a minimally invasive controller-synthesis procedure. However, barrier functions are yet to be robustified with respect to unmodeled disturbances (e.g., wheel slip or packet loss) in a manner conducive to real-time synthesis. As such, this paper formulates robust barrier functions for a general class of disturbed control-affine systems that, in turn, is key for the Robotarium to operate fully autonomously (i.e., without human supervision). Experimental results showcase the effectiveness of this robust formulation in a long-term experiment in the Robotarium.