{"title":"基于触觉的1-D可变形物体抓手定位","authors":"Amit Prigozin, A. Degani","doi":"10.1109/CASE49439.2021.9551534","DOIUrl":null,"url":null,"abstract":"As part of automation processes, robotic manipulators are occasionally required to assemble deformable objects, e.g., installing an O-ring into a groove. However, deformable objects are characterized by high uncertainty due to shape and length change under external forces. These uncertainties make the assembly process complex and slow and may lead to errors between the actual and desired gripping location. In this paper, we present a localization technique to estimate the actual gripping point by using the grid localization algorithm based on tactile sensing. To reduce the dependency on complex and relatively slow vision sensors, the pose estimation process is based only on tactile feedback, by recognizing features, e.g., corners, along the deformable object. In simulations and experiments, the proposed algorithm converged to the correct gripping point after three detected features with an accuracy of less than 1 mm.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tactile-Based Gripper Localization on 1-D Deformable Objects\",\"authors\":\"Amit Prigozin, A. Degani\",\"doi\":\"10.1109/CASE49439.2021.9551534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As part of automation processes, robotic manipulators are occasionally required to assemble deformable objects, e.g., installing an O-ring into a groove. However, deformable objects are characterized by high uncertainty due to shape and length change under external forces. These uncertainties make the assembly process complex and slow and may lead to errors between the actual and desired gripping location. In this paper, we present a localization technique to estimate the actual gripping point by using the grid localization algorithm based on tactile sensing. To reduce the dependency on complex and relatively slow vision sensors, the pose estimation process is based only on tactile feedback, by recognizing features, e.g., corners, along the deformable object. In simulations and experiments, the proposed algorithm converged to the correct gripping point after three detected features with an accuracy of less than 1 mm.\",\"PeriodicalId\":232083,\"journal\":{\"name\":\"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE49439.2021.9551534\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE49439.2021.9551534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tactile-Based Gripper Localization on 1-D Deformable Objects
As part of automation processes, robotic manipulators are occasionally required to assemble deformable objects, e.g., installing an O-ring into a groove. However, deformable objects are characterized by high uncertainty due to shape and length change under external forces. These uncertainties make the assembly process complex and slow and may lead to errors between the actual and desired gripping location. In this paper, we present a localization technique to estimate the actual gripping point by using the grid localization algorithm based on tactile sensing. To reduce the dependency on complex and relatively slow vision sensors, the pose estimation process is based only on tactile feedback, by recognizing features, e.g., corners, along the deformable object. In simulations and experiments, the proposed algorithm converged to the correct gripping point after three detected features with an accuracy of less than 1 mm.