让全尺寸人形机器人精准模仿人类动作并保持平衡
A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot
- 通过接触感知的全身动作重定向实现人类动作模仿
- 实时控制确保动作精度与抗干扰稳定性
- 适用于需要自然交互的机器人应用场景
运动模仿是人形机器人实现多样化复杂动作、提升表演自然度的关键方法。然而,人形机器人与人类在运动学和动力学上的显著差异,给精确模仿动作并维持平衡带来了重大挑战。本文提出一种面向全尺寸人形机器人的全身动作模仿框架。该方法采用接触感知的全身动作重定向技术,模仿人类动作并提供参考轨迹的初始值;同时,基于非线性质心模型预测控制器,在实时运行中确保动作准确性,维持平衡并克服外部扰动。全身控制器的辅助实现了更精确的力矩控制。在仿真和真实人形机器人上进行了多种人类动作的模仿实验,结果表明该方法具备高精度与强适应性,验证了其有效性。
原文摘要 · Abstract (English)
Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-like. However, the significant differences in kinematics and dynamics between humanoid robots and humans present a major challenge in accurately imitating motion while maintaining balance. In this paper, we propose a novel whole-body motion imitation framework for a full-size humanoid robot. The proposed method employs contact-aware whole-body motion retargeting to mimic human motion and provide initial values for reference trajectories, and the non-linear centroidal model predictive controller ensures the motion accuracy while maintaining balance and overcoming external disturbances in real time. The assistance of the whole-body controller allows for more precise torque control. Experiments have been conducted to imitate a variety of human motions both in simulation and in a real-world humanoid robot. These experiments demonstrate the capability of performing with accuracy and adaptability, which validates the effectiveness of our approach.
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