A General Safety Framework for Autonomous Manipulation in Human Environments

Abstract: Autonomous robots are projected to augment the manual workforce, especially in repetitive and hazardous tasks. For a successful deployment of such robots in human environments, it is crucial to guarantee human safety. State-of-the-art approaches to ensure human safety are either too restrictive to permit a natural human-robot collaboration or make strong assumptions that do not hold when for autonomous robots, e.g., knowledge of a pre-defined trajectory. Therefore, we propose SaRA-shield, a power and force limiting framework for AI-based manipulation in human environments that gives formal safety guarantees while allowing for fast robot speeds. As recent studies have shown that unconstrained collisions allow for significantly higher contact forces than constrained collisions (clamping), we propose to classify contacts by their collision type using reachability analysis. We then verify that the kinetic energy of the robot is below pain and injury thresholds for the detected collision type of the respective human body part in contact. Our real-world experiments show that SaRA-shield can effectively reduce the speed of the robot to adhere to injury-preventing energy limits.