文献类型：期刊文献

中文题名：基于体感的仿人机器人步态学习与控制

英文题名：Gait learning and control of humanoid robot based on Kinect

作者：周浩[1];浦剑涛[2];梁岚珍[1,2];方建军[2];郭浩[1]

第一作者：周浩

机构：[1]新疆大学电气工程学院;[2]北京联合大学自动化学院

第一机构：新疆大学电气工程学院,乌鲁木齐830047

年份：2015

卷号：35

期号：3

起止页码：787-791

中文期刊名：计算机应用

外文期刊名：Journal of Computer Applications

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD_E2015_2016】；

基金：北京市自然科学基金资助项目(4142018)

语种：中文

中文关键词：仿人机器人;步态规划;步态学习;零力矩点;体感

外文关键词：humanoid robot; gait planning; gait learning; Zero-Moment Point （ZMP） ; Kinect

摘要：针对现有理想化步态动力学模型规划方法复杂、人为指定参数过多、计算量大的问题,提出一种基于体感数据学习人体步态的仿人机器人步态生成方法。首先,用体感设备收集人体骨骼信息,基于最小二乘拟合方法建立人体关节局部坐标系;其次,搭建人体与机器人映射的运动学模型,根据两者间主要关节映射关系,生成机器人关节转角轨迹,实现机器人对人类行走姿态的学习;然后,基于零力矩点（ZMP）稳定性原则,对机器人脚踝关节转角采用梯度下降算法进行优化控制;最后,在步态稳定性分析上,提出使用安全系数来评价机器人行走稳定程度的方法。实验结果表明,步行过程中安全系数保持在0～0.85,期望为0.4825,ZMP接近于稳定区域中心,机器人实现了仿人姿态的稳定行走,证明了该方法的有效性。
To solve the problems of complex planning method, too many man-made specified parameters and huge computation in the existing gait dynamic model, the gait generation approach of humanoid robot based on the data collected by Kinect to learn human gait was proposed. Firstly, the skeleton information was collected by Kinect device, human joint local coordinate system was built by the least square fitting method. Next, the dynamic model of human body mapping robot was built, and robot joint angle trajectory was generated according to mapping relation between main joints, the studies of walking posture from human was realized. Then, Robot＇s ankle joint was optimized and controlled by gradient descent on the basis of Zero-Moment Point （ZMP） stability principle. Finally, on the gait stability analysis, safety factor was proposed to evaluate the stability of robot walk. The experimental results show that the safety factor of walking keeps in 0 to 0. 85, experctation is 0. 482 5 and ZMP closes to stable regional centres, the robot realizes walking imitating human posture and gait stability, which proves the validity of the method.