Tele-Running: Trajectory Generation for Monopod Robots by Teleoperation

Abstract

Energy-efficient legged locomotion in robots depends on exploiting passive dynamics, particularly with integrated mechanical compliance. Traditional model-based control strategies that leverage these dynamics often encounter challenges due to inherent model uncertainties. We propose a novel model-free method for generating motor trajectories in compliantly actuated monopods using teleoperation with force feedback. This approach allows operators to detect ground reaction forces and excite the robot's natural frequency, achieving highly efficient hopping. The method results in a mechanical Cost of Transport (CoT) of 0.25 at 0.63 m/s on an articulated hopper. To further enhance energy efficiency and adjust for hardware variations, these trajectories are refined using Black-Box Optimization (BBO) directly on the hardware. Experimental results confirm that these optimized trajectories closely match the efficiency of those initiated by humans, demonstrating the effectiveness of this method in exciting the robot's natural dynamics.