Viability-Preserving Passive Torque Control
This work addresses safety and performance issues in robotic manipulator control, representing an incremental improvement over existing constrained passive controllers.
The paper tackled the problem of safety violations in passivity-based torque controllers for manipulators under external perturbations by employing viability theory to pre-compute safe sets for constraints, resulting in higher control-loop rates and smoother trajectories compared to a baseline.
Conventional passivity-based torque controllers for manipulators are typically unconstrained, which can lead to safety violations under external perturbations. In this paper, we employ viability theory to pre-compute safe sets in the state-space of joint positions and velocities. These viable sets, constructed via data-driven and analytical methods for self-collision avoidance, external object collision avoidance and joint-position and joint-velocity limits, provide constraints on joint accelerations and thus joint torques via the robot dynamics. A quadratic programming-based control framework enforces these constraints on a passive controller tracking a dynamical system, ensuring the robot states remain within the safe set in an infinite time horizon. We validate the proposed approach through simulations and hardware experiments on a 7-DoF Franka Emika manipulator. In comparison to a baseline constrained passive controller, our method operates at higher control-loop rates and yields smoother trajectories.