Anticipatory and Adaptive Footstep Streaming for Teleoperated Bipedal Robots

TL;DR

This paper introduces a real-time, anticipatory footstep streaming method for teleoperated bipedal robots that improves synchronization, balance, and terrain adaptation by retargeting user steps and leveraging robot dynamics.

Contribution

It presents a novel approach that retargets user steps to robot footstep locations, anticipates user footsteps, and adapts to terrain, enhancing teleoperation performance.

Findings

Improved synchronization between user and robot steps.

Enhanced robot balance and stability during teleoperation.

Effective terrain adaptation demonstrated on humanoid robot Nadia.

Abstract

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.