基于质心校正补偿的仿人机器人模仿学习  

Humanoid Robot Imitation Learning Based on COM Correction and Compensation

作　　者：于建均 张远 左国玉 阮晓钢 吴鹏申 

机构地区：[1]北京工业大学信息学部,北京100124 [2]计算智能与智能系统北京市重点实验室,北京100124

出　　处：《北京工业大学学报》2018年第2期193-199,共7页Journal of Beijing University of Technology

基　　金：国家自然科学基金资助项目(61375086);高等学校博士学科点专项科研基金资助项目(20101103110007);北京工业大学智能制造领域大科研推进计划资助项目

摘　　要：由于仿人机器人自由度多、结构冗余,因此面对不同环境下的运动规划十分复杂.利用人体运动信息作为示教数据,实现仿人机器人对人体姿态的模仿学习,简化了仿人机器人的运动规划.为满足机器人在运动过程中的平衡性,提出了一种机器人质心补偿的方法:通过示教数据预估机器人的质心偏移,经质心-角度雅可比矩阵计算角度补偿量,并引入二次规划进行优化处理.基于Nao机器人的模仿学习系统实验研究结果表明:提出的质心补偿方法可以有效地保证机器人在模仿学习过程中的姿态平衡,引入的权值可调的二次规划有效地保证了姿态模仿的相似性.Since humanoid robot has high degrees of freedom and redundant structure, so the motion planning is complicated when facing different environments. In this paper, kinect was used to collect human motion information as teaching data to conduct the imitation of human motion. The motion planning of humanoid robot was simplified. To maintain the balance of robot in the process of motion, a method was proposed to compensate the robot’s center of mass （COM）： estimate the deviation of mass center through teaching dat was estimated,and the calculation of angle compensation through Jacobian was conducted and quadratic programming for optimization was optimized. The experiment of imitation system based on robot Nao indicates that the method of COM compensation ensures the balance in the process of imitation,the quadratic programming can effectively ensure the similarity of motion imitation.

关 键 词：仿人机器人 模仿学习 质心预估 雅可比矩阵 姿态映射 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]