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.

翻译：本文针对可靠且安全的人机协作场景，开发了协作式双臂操作技术，支持远程及本地操作员协同完成双臂任务。我们提出了一种最优运动适配方法，可将来自多位操作员的任意指令重新映射为可行的控制参考。该协作操作框架包含三个核心模块：(1) 基于导纳控制的接触力调节模块，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，通过满足任务约束及机器人物理极限，将多位操作员的交互指令适配为可行运动；(3) 基于分形阻抗控制的交互控制器，该控制器对时延具有鲁棒性，可稳定叠加多个控制信号以生成期望关节力矩并控制双臂机器人。大量实验验证了该协作双臂框架的能力，包括：(1) 双臂遥操作中，相较于未采用所提优化方法时出现的故障，该框架可将违反关节力矩极限的任意不可行指令适配为安全范围内的连续操作；(2) 在模型不精确条件下，通过物理交互稳健操作叠放物体；(3) 多操作员协同部件装配及远程工业连接器插入作业，验证了稳定可靠的人机共融操作性能。