为冗余机械臂设计多层安全框架，兼顾避障与碰撞应对能力。
Multi-layered Safety of Redundant Robot Manipulators via Task-oriented Planning and Control
- 基于多射击模型预测控制的任务导向轨迹规划
- 仅用本体感知数据实现碰撞时的稳定响应与抗干扰
- 适用于开放空间中存在未知障碍的机器人操作场景
确保机器人机械臂在开放工作空间中的安全性至关重要。传感器误差或不可预测的碰撞使环境充满不确定性。本文研究冗余机械臂面临的潜在安全挑战，提出一种任务导向的规划与控制框架，实现多层安全的同时保持高效任务执行。该方法包含两部分：基于多射击模型预测控制（MPC）的任务导向轨迹规划器，以及仅依赖本体感知数据实现安全高效碰撞反应的力矩控制器。通过大量仿真和真实硬件实验，验证了该框架能有效应对静态或动态不确定障碍，并在意外接触发生时表现出良好的扰动抵抗能力。
原文摘要 · Abstract (English)
Ensuring safety is crucial to promote the application of robot manipulators in open workspaces. Factors such as sensor errors or unpredictable collisions make the environment full of uncertainties. In this work, we investigate these potential safety challenges on redundant robot manipulators, and propose a task-oriented planning and control framework to achieve multi-layered safety while maintaining efficient task execution. Our approach consists of two main parts: a task-oriented trajectory planner based on multiple-shooting model predictive control (MPC) method, and a torque controller that allows safe and efficient collision reaction using only proprioceptive data. Through extensive simulations and real-hardware experiments, we demonstrate that the proposed framework can effectively handle uncertain static or dynamic obstacles, and perform disturbance resistance in manipulation tasks when unforeseen contacts occur.
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