让机器人提前预判并自适应用户脚步，实现稳定高速远程行走
Anticipatory and Adaptive Footstep Streaming for Teleoperated Bipedal Robots
- 用机器人自身动力学重定向用户步态，提升稳定性
- 预判用户下一步位置，延迟缩短至100毫秒内
- 自动适应复杂地形，适合真实环境远程操控
在远程操控中实现人机运动的无缝同步，尤其是在高速任务下仍具挑战。本文提出一种实时传递步态动作的新方法：不直接复制用户脚部姿态，而是将用户步态重定向至机器人步点位置，使机器人利用自身动力学完成行走，保障平衡与稳定。该方法可预判用户下一步落脚点，显著减少从用户启动到机器人执行的延迟。步态估计持续调整以逼近用户实际参考值。系统还能自主调节机器人步幅以适应周围地形差异，克服用户在平坦地面操作而机器人身处不平地形带来的环境错配问题。在人形机器人Nadia上的实验验证了该系统的有效性。
原文摘要 · Abstract (English)
Achieving seamless synchronization between user and robot motion in teleoperation, particularly during high-speed tasks, remains a significant challenge. In this work, we propose a novel approach for transferring stepping motions from the user to the robot in real-time. Instead of directly replicating user foot poses, we retarget user steps to robot footstep locations, allowing the robot to utilize its own dynamics for locomotion, ensuring better balance and stability. Our method anticipates user footsteps to minimize delays between when the user initiates and completes a step and when the robot does it. The step estimates are continuously adapted to converge with the measured user references. Additionally, the system autonomously adjusts the robot's steps to account for its surrounding terrain, overcoming challenges posed by environmental mismatches between the user's flat-ground setup and the robot's uneven terrain. Experimental results on the humanoid robot Nadia demonstrate the effectiveness of the proposed system.
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