机器人灵巧手抓持分类器的设计与实现  

DESIGN AND IMPLEMENT A SYSTEM OF GRASP IDENTIFICATION FOR DEXTEROUS ROBOT HAND

作　　者：刘杰[1] 张玉茹[1] 

机构地区：[1]北京航空航天大学机器人研究所,北京100083

出　　处：《机器人》2003年第3期259-263,共5页Robot

基　　金：国家自然科学基金 ( 5 9985 0 0 1);国家教育部博士点基金 ( 2 0 0 0 0 0 0 60 5 )资助项目

摘　　要：机器人灵巧手的抓持分类是抓持规划的一个主要问题 .本文应用模式识别技术设计和实现了一种基于高斯混合模型 GMM的分类器 .采用 Expectation Maximization(EM)算法估计 GMM的参数 ,对人手的抓持动作进行识别与分类 ,经过人手到机器人手的关节空间运动映射 ,实现了机器人灵巧手的抓持动作分类 .The grasp taxonomy is one of the key problems in grasp planning of dexterous robot hands. This paper describes the design and implement of a system of grasp identification based on pattern recognition technology. The feature of human grasp is represented by Gaussian Mixture Model (GMM). The parameters of GMM are estimated by the Expectation Maximization algorithm (EM). The taxonomy of robot hand grasps is achieved by mapping grasps from human hand to robot hand. The effectiveness of the GMM identification method is proved by the experiments. The system can be used in grasp planning.

关 键 词：机器人灵巧手 抓持分类器 设计 模式识别 高斯混合模型 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]