Anticipatory and Adaptive Footstep Streaming for Teleoperated Bipedal Robots

2025-08-15

AI Summary

Remote teleoperation of bipedal robots in high-speed tasks suffers from master-slave motion asynchrony and environmental inconsistency, severely compromising stability. To address this, we propose a real-time teleoperation framework integrating gait prediction and adaptive motion retargeting. Our approach features: (1) a user foot-motion dynamic prediction model for proactive intent estimation; (2) a real-time step-position retargeting mechanism with convergence-based adjustment to mitigate kinematic discrepancies between master and slave; and (3) a terrain-aware module enabling online, adaptive gait parameter modulation. Experiments on the Nadia humanoid platform demonstrate substantial improvements: end-to-end latency is reduced to under 80 ms; step-phase synchronization error decreases by 42%; and balance robustness on complex terrain is significantly enhanced. The framework provides a scalable, generalizable solution for high-dynamics bipedal teleoperation.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

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.

Problem

• Real-time teleoperation synchronization for bipedal robots
• Adaptive footstep retargeting for robot stability
• Terrain mismatch compensation in remote locomotion

Innovation

• Retargets user steps to robot footstep locations
• Anticipates footsteps to minimize motion delays
• Autonomously adjusts steps for terrain adaptation