FastMimic: Model-Based Motion Imitation for Agile, Diverse and Generalizable Quadrupedal Locomotion

Author:

Li Tianyu1,Won Jungdam2,Cho Jeongwoo3ORCID,Ha Sehoon1,Rai Akshara4

Affiliation:

1. School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA

2. Department of Computer Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea

3. School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

4. Meta AI, Menlo Park, CA 94025, USA

Abstract

Robots operating in human environments require a diverse set of skills, including slow and fast walking, turning, side-stepping, and more. However, developing robot controllers capable of exhibiting such a broad range of behaviors is a challenging problem that necessitates meticulous investigation for each task. To address this challenge, we introduce a trajectory optimization method that resolves the kinematic infeasibility of reference animal motions. This method, combined with a model-based controller, results in a unified data-driven model-based control framework capable of imitating various animal gaits without the need for expensive simulation training or real-world fine-tuning. Our framework is capable of imitating a variety of motor skills such as trotting, pacing, turning, and side-stepping with ease. It shows superior tracking capabilities in both simulations and the real world compared to other imitation controllers, including a model-based one and a learning-based motion imitation technique.

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. SLoMo: A General System for Legged Robot Motion Imitation From Casual Videos;IEEE Robotics and Automation Letters;2023-11

2. Learning a Single Policy for Diverse Behaviors on a Quadrupedal Robot Using Scalable Motion Imitation;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

3. Special Issue “Legged Robots into the Real World”;Robotics;2023-07-13

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