Passivity is necessary for robots to fluidly collaborate and interact with humans physically. Nevertheless, due to the unconstrained nature of passivity-based impedance control laws, the robot is vulnerable to infeasible and unsafe configurations upon physical perturbations. In this paper, we propose a novel control architecture that allows a torque-controlled robot to guarantee safety constraints such as kinematic limits, self-collisions, external collisions and singularities and is passive only when feasible. This is achieved by constraining a dynamical system based impedance control law with a relaxed hierarchical control barrier function quadratic program subject to multiple concurrent, possibly contradicting, constraints. Joint space constraints are formulated from efficient data-driven self- and external C^2 collision boundary functions. We theoretically prove constraint satisfaction and show that the robot is passive when feasible. Our approach is validated in simulation and real robot experiments on a 7DoF Franka Research 3 manipulator.

翻译：被动性对于机器人实现流畅的人机物理协作与交互至关重要。然而，由于基于被动性的阻抗控制律缺乏约束性，机器人易因物理扰动而陷入不可行或不安全的构型。本文提出一种新型控制架构，使得力矩控制机器人能够保证运动学极限、自碰撞、外部碰撞及奇异性等安全约束，且仅在可行状态下保持被动性。该架构通过将基于动力系统的阻抗控制律与松弛层级控制屏障函数二次规划相结合实现，该二次规划需同时处理多个并发且可能相互矛盾的约束。关节空间约束由高效数据驱动的自碰撞与外部碰撞C²碰撞边界函数构建。我们理论上证明了约束满足性，并表明机器人在可行状态下具有被动性。该方法在7自由度Franka Research 3操作器上通过仿真与实物实验得到验证。