Teleoperation has emerged as an alternative solution to fully-autonomous systems for achieving human-level capabilities on humanoids. Specifically, teleoperation with whole-body control is a promising hands-free strategy to command humanoids but demands more physical and mental effort. To mitigate this limitation, researchers have proposed shared-control methods incorporating robot decision-making to aid humans on low-level tasks, further reducing operation effort. However, shared-control methods for wheeled humanoid telelocomotion on a whole-body level has yet to be explored. In this work, we study how whole-body feedback affects the performance of different shared-control methods for obstacle avoidance in diverse environments. A Time-Derivative Sigmoid Function (TDSF) is proposed to generate more intuitive force feedback from obstacles. Comprehensive human experiments were conducted, and the results concluded that force feedback enhances the whole-body telelocomotion performance in unfamiliar environments but could reduce performance in familiar environments. Conveying the robot's intention through haptics showed further improvements since the operator can utilize the force feedback for short-distance planning and visual feedback for long-distance planning.
翻译:远程操作已成为实现人体人的能力的全面自主系统的一种替代解决办法。具体地说,全体控制的远程操作是一种充满希望的无手控制战略,可以指挥人体,但要求作出更多的身心努力。为减轻这一限制,研究人员提出了采用机器人决策的共享控制方法,以帮助人类完成低层次的任务,进一步减少操作努力。然而,整个机体水平的轮式人类远程移动的共享控制方法尚未探索。在这项工作中,我们研究了整体反馈如何影响不同共同控制方法的绩效,以在不同环境中避免障碍。建议从障碍中产生更多的直觉力量反馈。进行了全面的人类实验,其结论是,强力反馈可以提高不熟悉环境中的全体远程移动性能,但可以降低熟悉环境中的性能。通过机能将机器人的用意感转化出来,显示出进一步的改进,因为操作者可以利用力量反馈进行短距离规划和长距离规划的视觉反馈。