Ensuring operational safety is critical for human-to-humanoid motion imitation. This paper presents a vision-based framework that enables a humanoid robot to imitate human movements while avoiding collisions. Human skeletal keypoints are captured by a single camera and converted into joint angles for motion retargeting. Safety is enforced through a Control Barrier Function (CBF) layer formulated as a Quadratic Program (QP), which filters imitation commands to prevent both self-collisions and human-robot collisions. Simulation results validate the effectiveness of the proposed framework for real-time collision-aware motion imitation.

翻译：确保操作安全对于人到人形机器人的运动模仿至关重要。本文提出一种基于视觉的框架，使人形机器人能够模仿人类运动同时避免碰撞。通过单摄像头捕获人体骨骼关键点，并将其转换为关节角度以进行运动重定向。安全性通过基于二次规划的控制屏障函数层实现，该层过滤模仿指令以防止自碰撞和人机碰撞。仿真结果验证了所提框架在实时碰撞感知运动模仿中的有效性。