提升远程操控人形机器人时躯干与手臂的协同效率
Human-Robot Collaboration for the Remote Control of Mobile Humanoid Robots with Torso-Arm Coordination
- 人类发起：手动控制躯干，机器人自主协调手臂
- 机器人发起：根据可达性、任务目标自动规划协同动作
- 17人实验验证，机器人主导更高效且用户偏好高
近年来，越来越多的人形机器人被部署在医院和养老环境中，通常由人工远程操作。其运动学冗余提升了可达性和操作能力，使机器人能在复杂杂乱环境中导航并完成多种任务。然而，这种冗余也带来了显著的控制挑战，尤其是在协调机器人的宏观-微观结构（躯干与手臂）方面。为此，本文提出多种人机协同（HRC）方法，用于协调远程操控移动人形机器人中的躯干与手臂，旨在平衡自主性与人工输入，以提升系统效率与任务执行能力。方法包括人类发起型（用户手动控制躯干）和机器人发起型（基于可达性、任务目标或推断的人类意图，自主协调躯干与手臂）。我们通过包含17名参与者的用户研究，对比了不同方法在任务表现、操作能力和能耗效率方面的差异，并分析了用户的偏好。
原文摘要 · Abstract (English)
Recently, many humanoid robots have been increasingly deployed in various facilities, including hospitals and assisted living environments, where they are often remotely controlled by human operators. Their kinematic redundancy enhances reachability and manipulability, enabling them to navigate complex, cluttered environments and perform a wide range of tasks. However, this redundancy also presents significant control challenges, particularly in coordinating the movements of the robot's macro-micro structure (torso and arms). Therefore, we propose various human-robot collaborative (HRC) methods for coordinating the torso and arm of remotely controlled mobile humanoid robots, aiming to balance autonomy and human input to enhance system efficiency and task execution. The proposed methods include human-initiated approaches, where users manually control torso movements, and robot-initiated approaches, which autonomously coordinate torso and arm based on factors such as reachability, task goal, or inferred human intent. We conducted a user study with N=17 participants to compare the proposed approaches in terms of task performance, manipulability, and energy efficiency, and analyzed which methods were preferred by participants.
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