基于虚拟力引导的人机协同目标抓取方法

针对力反馈遥操作中传统人工势场法无法适应于机械臂整体的避障以及在作业过程中操作者难以控制机械臂到达所需位姿的问题，提出了一种基于虚拟力引导的人机协同目标抓取方法。力反馈设备向操作者提供力觉交互。通过结合人工势场法和虚拟夹具，构建管道形虚拟力场，生成实时虚拟力引导，实现协助操作者完成从端机器人的整体避障任务并在完成避障后引导机器人返回预定义路径并趋近目标点。当进行抓取任务时，构建锥形虚拟力场，实现协助操作者操作机械臂到达目标位置和姿态。此外，提出了一种机器人运动限制方法以降低操作者的操作失误对抓取任务的影响。实验证明，该方法能有效提高目标抓取操作的成功率和操作效率。

Human-machine cooperative object grasping method based on virtual force guidance

The traditional artificial potential field method in force feedback teleoperation cannot adapt to the overall obstacle avoidance of manipulators, and operators find it difficult to control manipulators to reach the required pose in the operation process. Accordingly, this paper proposes a human-machine cooperative object grasping method based on virtual force guidance. Force feedback devices provide operators with haptic interaction. By combining the artificial potential field method and virtual fixture and by constructing a pipe-like virtual force field, the real-time virtual force guidance is generated, which can assist operators in completing the overall obstacle avoidance tasks of slave robots and guide robots to return to the predefined path and approach the target point after completing their tasks. When a grasping task is performed, a virtual cone-shaped force field is constructed to help operators make manipulators reach the target position and pose. In addition, a method of limiting robot motion is proposed to reduce the impact of operators’ errors on their grasping tasks. Experimental results show that this method can effectively improve the success rate and efficiency of object grasping operation.