In this work we consider the current certification process of applications with physical human–robot interaction (pHRI). Two major hazards are collisions and clamping scenarios. The implementation of safety measures in pHRI applications typically depends strongly on coordinates, e.g., to monitor the robot velocity or to predict external forces. We show that the current certification process does not, in general, guarantee a safe robot behavior. In particular, in unstructured environments it is not possible to predict all risks in advance. We therefore propose to control the energy of the robot, which is a coordinate invariant entity. For an impedance controlled robot, the total energy consists of potential energy and kinetic energy. The energy flow from task description to physical interaction follows a strict causality. We assign a safe energy budget for the robot. With this energy budget, the presented controller auto-tunes its parameters to limit the exchanged kinetic energy during a collision and the potential energy during clamping scenarios. In contact, the robot behaves compliantly and therefore eliminates clamping danger. After contact, the robot automatically continues to follow the desired trajectory. With this approach the number of safety-related parameters to be determined can be reduced to one energy value, which has the potential to significantly speed up the commissioning of pHRI applications. The proposed technique is validated by experiments.

在这项工作中，我们考虑了具有物理人机交互（pHRI）的应用程序的当前认证过程。两种主要危险是碰撞和夹紧情况。pHRI应用程序中安全措施的实施通常在很大程度上取决于坐标，例如，监视机器人速度或预测外力。我们证明，当前的认证流程通常不能保证机器人行为的安全。特别是在非结构化环境中，不可能预先预测所有风险。因此，我们建议控制机器人的能量，该能量是坐标不变实体。对于阻抗受控的机器人，总能量由势能和动能组成。从任务描述到物理交互的能量流遵循严格的因果关系。我们为机器人分配安全的能源预算。利用此能量预算，所提出的控制器会自动调整其参数，以限制碰撞过程中交换的动能和夹紧情况下的势能。接触时，机器人行为顺应，因此消除了夹紧危险。接触后，机器人将自动继续遵循所需的轨迹。通过这种方法，可以将要确定的安全相关参数的数量减少到一个能量值，这有可能显着加快pHRI应用程序的调试速度。实验验证了所提出的技术。接触时，机器人行为顺应，因此消除了夹紧危险。接触后，机器人将自动继续遵循所需的轨迹。通过这种方法，可以将要确定的安全相关参数的数量减少到一个能量值，这有可能显着加快pHRI应用程序的调试速度。实验验证了所提出的技术。接触时，机器人行为顺应，因此消除了夹紧危险。接触后，机器人将自动继续遵循所需的轨迹。通过这种方法，可以将要确定的安全相关参数的数量减少到一个能量值，这有可能显着加快pHRI应用程序的调试速度。实验验证了所提出的技术。