Viability-Preserving Passive Torque Control
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911533242515456 |
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| author | Zhang, Zizhe Wang, Yicong Zhang, Zhiquan Li, Tianyu Figueroa, Nadia |
| author_facet | Zhang, Zizhe Wang, Yicong Zhang, Zhiquan Li, Tianyu Figueroa, Nadia |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_03367 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Viability-Preserving Passive Torque Control Zhang, Zizhe Wang, Yicong Zhang, Zhiquan Li, Tianyu Figueroa, Nadia Systems and Control Machine Learning Robotics 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. |
| title | Viability-Preserving Passive Torque Control |
| topic | Systems and Control Machine Learning Robotics |
| url | https://arxiv.org/abs/2510.03367 |