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.

翻译：自主机器人有望增强人工劳动力，特别是在重复性和危险性任务中。为使此类机器人在人机交互环境中成功部署，保障人类安全至关重要。现有确保人类安全的方法要么限制过严而无法实现自然的人机协作，要么基于某些不适用于自主机器人的强假设（例如预设轨迹的精确已知性）。为此，我们提出SaRA-shield——一种面向人机交互环境中基于人工智能操作的功率与力限制框架，该框架在保证形式化安全性的同时允许机器人高速运行。鉴于近期研究表明无约束碰撞产生的接触力显著高于约束碰撞（夹持碰撞），我们提出通过可达性分析对接触类型进行碰撞分类。随后验证机器人的动能是否低于对应接触人体部位在检测碰撞类型下的疼痛与损伤阈值。实际实验表明，SaRA-shield能有效降低机器人运行速度以符合预防损伤的能量限值。