English

Viability-Preserving Passive Torque Control

Systems and Control 2026-03-24 v2 Machine Learning Robotics Systems and 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.

Keywords

Cite

@article{arxiv.2510.03367,
  title  = {Viability-Preserving Passive Torque Control},
  author = {Zizhe Zhang and Yicong Wang and Zhiquan Zhang and Tianyu Li and Nadia Figueroa},
  journal= {arXiv preprint arXiv:2510.03367},
  year   = {2026}
}

Comments

8 pages, 7 figures, Project Website: https://vpp-tc.github.io/webpage/

R2 v1 2026-07-01T06:16:00.330Z