Haptic shared control enables a human operator and an autonomous controller to share the control of a robotic system using haptic active constraints. It has been used in robotic teleoperation for different purposes, such as navigating along paths minimizing the torques requested to the manipulator or avoiding possibly dangerous areas of the workspace. However, few works have focused on using these ideas to account for the user's comfort. In this article, we present an innovative haptic-enabled shared control approach aimed at minimizing the user's workload during a teleoperated manipulation task. Using an inverse kinematic model of the human arm and the rapid upper limb assessment (RULA) metric, the proposed approach estimates the current user's comfort online. From this measure and an a priori knowledge of the task, we then generate dynamic active constraints guiding the users towards a successful completion of the task, along directions that improve their posture and increase their comfort. Studies with human subjects show the effectiveness of the proposed approach, yielding a 30% perceived reduction of the workload with respect to using standard guided human-in-the-loop teleoperation.

中文翻译：

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关心人类操作员：触觉共享控制可提高机器人远程操作中的用户舒适度

触觉共享控制使人类操作员和自主控制器能够使用触觉主动约束共享机器人系统的控制。它已用于机器人远程操作的不同目的，例如沿路径导航以最大限度地减少对机械手的扭矩要求或避免工作区中可能存在的危险区域。然而，很少有作品专注于使用这些想法来考虑用户的舒适度。在本文中，我们提出了一种创新的支持触觉的共享控制方法，旨在最大限度地减少用户在远程操作任务期间的工作量。使用人体手臂的逆运动学模型和快速上肢评估 (RULA) 指标，所提出的方法在线估计当前用户的舒适度。从这个度量和任务的先验知识，然后我们生成动态的主动约束，引导用户成功完成任务，沿着改善他们的姿势和增加他们的舒适度的方向。对人类受试者的研究显示了所提议方法的有效性，相对于使用标准引导的人在环远程操作，工作量减少了 30%。