保持可行性被动扭矩控制
Viability-Preserving Passive Torque Control
AI总结：
本文利用可行性理论预计算关节位置和速度的状态空间安全集，通过数据驱动和分析方法避免自碰撞和外部物体碰撞，约束关节加速度从而限制扭矩，通过二次规划框架确保机器人状态在无限时间范围内保持安全。
摘要：
传统基于被动性的机械臂扭矩控制器通常是无约束的，这可能导致在外部扰动下发生安全违规。本文利用可行性理论预先计算状态空间中关节位置和速度的安全集。这些可行集通过数据驱动和分析方法构建，用于自我碰撞避免、外部物体碰撞避免以及关节位置和速度限制。这些可行集通过机器人动力学提供对关节加速度的约束，从而限制扭矩。基于二次规划的控制框架强制这些约束在被动控制器跟踪动态系统时生效，确保机器人状态在无限时间范围内保持在安全集内。我们通过仿真实验和硬件实验在7自由度Franka Emika机械臂上验证了所提出的方法。与基线约束被动控制器相比，本文方法在控制循环速率上更高，并产生更平滑的轨迹。
英文摘要：
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.
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