{"ID":2860783,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03367","arxiv_id":"2510.03367","title":"Viability-Preserving Passive Torque Control","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2510.03367","url_pdf":"https://arxiv.org/pdf/2510.03367v2","authors":"[\"Zizhe Zhang\",\"Yicong Wang\",\"Zhiquan Zhang\",\"Tianyu Li\",\"Nadia Figueroa\"]","published":"2025-10-03T04:50:00Z","proceeding":"eess.SY","tasks":"[\"eess.SY\",\"cs.LG\",\"cs.RO\"]","methods":"[]","has_code":false}