{"title":"手握任务机械手的自动化设计","authors":"Christopher Hazard, N. Pollard, Stelian Coros","doi":"10.1109/HUMANOIDS.2018.8624932","DOIUrl":null,"url":null,"abstract":"Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a preexisting kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high level objectives as input. Our goal is to create a pipeline that automatically generates custom hands designed for specific manipulation tasks based on high level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automated Design of Manipulators for In-Hand Tasks\",\"authors\":\"Christopher Hazard, N. Pollard, Stelian Coros\",\"doi\":\"10.1109/HUMANOIDS.2018.8624932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a preexisting kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high level objectives as input. Our goal is to create a pipeline that automatically generates custom hands designed for specific manipulation tasks based on high level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty.\",\"PeriodicalId\":433345,\"journal\":{\"name\":\"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HUMANOIDS.2018.8624932\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HUMANOIDS.2018.8624932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated Design of Manipulators for In-Hand Tasks
Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a preexisting kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high level objectives as input. Our goal is to create a pipeline that automatically generates custom hands designed for specific manipulation tasks based on high level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty.