{"title":"Kinematic Redundancy in Robot Grasp Synthesis. An Efficient Tree-based Representation","authors":"C. F. Peris, Ó. Reinoso, M. A. Vicente, R. Aracil","doi":"10.1109/ROBOT.2005.1570276","DOIUrl":null,"url":null,"abstract":"A redundancy resolution technique devoted to grasp synthesis is presented. Given a set of contact points and a certain robot arm and gripper, the goal is to select both the best assignment of gripper fingers to contact points and the best joint values that allow the fingers to reach such contact points. The system proposed is based on the generation of an inverse kinematics tree where fast searches can be performed in order to find the optimum configuration. Optimality is defined as similarity to previously stored examples over a hierarchical structure of configuration data, which includes finger assignments and robot joints.","PeriodicalId":350878,"journal":{"name":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOT.2005.1570276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A redundancy resolution technique devoted to grasp synthesis is presented. Given a set of contact points and a certain robot arm and gripper, the goal is to select both the best assignment of gripper fingers to contact points and the best joint values that allow the fingers to reach such contact points. The system proposed is based on the generation of an inverse kinematics tree where fast searches can be performed in order to find the optimum configuration. Optimality is defined as similarity to previously stored examples over a hierarchical structure of configuration data, which includes finger assignments and robot joints.