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arXiv 2206.00528cs.RO
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基于最优运动适配与交互控制的协作式双臂操作

Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control

University of Edinburgh（爱丁堡大学）；University College London（伦敦大学学院）；University of Sussex（萨塞克斯大学）

Ruoshi Wen, Quentin Rouxel, Michael Mistry, Zhibin Li, Carlo Tiseo

备注：
in IEEE Robotics & Automation Magazine, 2023
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AI总结：

本研究提出含最优运动适配与分形阻抗交互控制的协作双臂操作框架，可将多操作员指令适配为机器人可行运动，经多场景实验验证能实现安全可靠的人机协同双臂操作。

摘要：

本研究开发了用于可靠、安全人机协作的协作式双臂操作技术，可支持远程与本地人类操作员交互协作完成双臂任务。我们提出一种最优运动适配方法，将多名人类操作员的任意指令重定向为可行的控制参考量。该协作操作框架包含三大核心模块：（1）接触力调制模块，通过导纳控制实现与物体的柔顺物理交互；（2）任务空间序列平衡与逆运动学优化模块，通过满足机器人的任务约束与物理极限，将多名操作员的交互指令适配为可行运动；（3）交互控制器，基于分形阻抗控制实现，对时间延迟具有鲁棒性，且能稳定叠加多种控制作用，生成所需关节力矩以控制双臂机器人。大量实验验证了该协作双臂框架的性能：（1）双臂遥操作场景中，所提优化可将违反关节力矩极限的任意不可行指令适配为安全边界内的连续操作，而无该优化时会出现操作失败；（2）存在模型不准确性的情况下，可通过物理交互稳健操控堆叠物体；（3）多操作员协作零件装配、遥操作工业连接器插入任务，验证了可靠人机协同操作的稳定性能保证。

英文摘要：

This work developed collaborative bimanual manipulation for reliable and safe human-robot collaboration, which allows remote and local human operators to work interactively for bimanual tasks. We proposed an optimal motion adaptation to retarget arbitrary commands from multiple human operators into feasible control references. The collaborative manipulation framework has three main modules: (1) contact force modulation for compliant physical interactions with objects via admittance control; (2) task-space sequential equilibrium and inverse kinematics optimization, which adapts interactive commands from multiple operators to feasible motions by satisfying the task constraints and physical limits of the robots; and (3) an interaction controller adopted from the fractal impedance control, which is robust to time delay and stable to superimpose multiple control efforts for generating desired joint torques and controlling the dual-arm robots. Extensive experiments demonstrated the capability of the collaborative bimanual framework, including (1) dual-arm teleoperation that adapts arbitrary infeasible commands that violate joint torque limits into continuous operations within safe boundaries, compared to failures without the proposed optimization; (2) robust maneuver of a stack of objects via physical interactions in presence of model inaccuracy; (3) collaborative multi-operator part assembly, and teleoperated industrial connector insertion, which validate the guaranteed stability of reliable human-robot co-manipulation.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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