A Real-Time Upper-Body Robot Imitation System

Zhijun Zhang, Yaru Niu, Lingdong Kong, Shuyang Lin, Wang Hao
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引用次数: 5

Abstract

An upper-body robot imitation (UBRI) system is proposed and developed to enable the human upper body imitation by a humanoid robot in real time. To achieve the imitation of arm motions, a geometry-based analytical method is presented and applied to extracting the joint angles of the human and mapping to the robot. Comparing to the traditional numerical methods of inverse kinematic computations, the geometrical analysis method generates a lower computational cost and maintains good imitation similarity. To map the human head motions to the head of the humanoid robot, a face tracking algorithm is employed to recognize the human face and track the human head poses in real time. A hand extraction and hand state recognition algorithm is proposed to achieve the hand motion mapping. At last, the completion rate and similarity evaluation experiments are conducted to verify the effectiveness of the proposed UBRI system.
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一种实时上肢机器人仿真系统
为实现仿人机器人对人体上半身的实时模仿,提出并开发了一种上半身机器人仿真系统。为了实现对手臂运动的模仿,提出了一种基于几何的解析方法,并将其应用于人体关节角的提取和映射到机器人上。与传统的运动学逆计算数值方法相比,几何分析方法的计算成本更低,并且保持了较好的仿真相似性。为了将人的头部运动映射到人形机器人的头部,采用人脸跟踪算法对人脸进行识别,并实时跟踪人的头部姿态。为了实现手部运动映射,提出了一种手部提取和手部状态识别算法。最后,通过完成率和相似度评价实验验证了所提UBRI系统的有效性。
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