In-between Motion Generation Based Multi-Style Quadruped Robot Locomotion

TL;DR

This paper presents a novel framework for quadruped robot locomotion that generates diverse, physically plausible multi-style motions between arbitrary states, improving stability and velocity tracking, and validated on real robots.

Contribution

Introduces a CVAE-based motion generator for multi-style locomotion synthesis, enabling versatile and physically feasible movements between arbitrary states.

Findings

Enhanced velocity tracking performance.

Improved deployment stability.

Successful real-world robot deployment.

Abstract

Quadruped robots face persistent challenges in achieving versatile locomotion due to limitations in reference motion data diversity. To address these challenges, we introduce an in-between motion generation based multi-style quadruped robot locomotion framework. We propose a CVAE based motion generator, synthesizing multi-style dynamically feasible locomotion sequences between arbitrary start and end states. By embedding physical constraints and leveraging joint poses based phase manifold continuity, this component produces physically plausible motions spanning multiple gait modalities while ensuring kinematic compatibility with robotic morphologies. We train the imitation policy based on generated data, which validates the effectiveness of generated motion data in enhancing controller stability and improving velocity tracking performance. The proposed framework demonstrates significant improvements in velocity tracking and deployment stability. We successfully deploy the framework on a real-world quadruped robot, and the experimental validation confirms the framework's capability to generate and execute complex motion profiles, including gallop, tripod, trotting and pacing.