arXiv Computer Vision By Sheng Wu, Guoqiang Zhao, Zhe Yang, Fei Teng, Zhikun Zhou, Yanlin Yang, Zheng Fang, Hong Zheng, Yaonan Wang, Kailun Yang

OmniMimic: Dynamics-completed Motion Augmentation for Multi-style Omnidirectional Quadruped Locomotion

Read the original on arXiv Computer Vision →

OmniMimic is a training framework that expands limited animal demonstration data into a single multi‑gait policy for omnidirectional quadruped locomotion. It uses temporal reversal, constrained dynamics completion, and sagittal reflection to generate kinematic and physical supervision beyond the observed directions, then progressively expands command ranges and employs a shared actor with soft‑gated gait‑specialized residual experts. In simulation, OmniMimic improves foot‑position accuracy by 12.9% and velocity‑tracking error by 63.1% over the APEX baseline across four gaits.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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