{"title":"Preliminary Implementation of Grasping Operation by a Collaborative Robot Arm: Using a Ball as Example","authors":"Wen-Chang Cheng, Chien-Hung Lin, Cheng-Yi Shi, Hung-Chou Hsiao, Chun-Lung Chang","doi":"10.1109/taai54685.2021.00062","DOIUrl":null,"url":null,"abstract":"Grasping objects is one of the basic functions of a robot arm. This study completed the implementation of the process in which a collaborative robot (cobot) arm grasps an object. Hardware components included a depth camera, cobot arm, and artificial intelligence equipment for edge computing. Software components included computer visualization techniques, deep learning, and robot operating system. To complete the preliminary implementation of the system, the grasping operation of the robot arm was set to target a ball. This system implementation sheds light on how robot arms and deep learning techniques are applied to real-life problems. Experiments verified that the preliminary system implemented was able to correctly complete the ball-grasping operation and achieve the pragmatic goal.","PeriodicalId":343821,"journal":{"name":"2021 International Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Technologies and Applications of Artificial Intelligence (TAAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/taai54685.2021.00062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Grasping objects is one of the basic functions of a robot arm. This study completed the implementation of the process in which a collaborative robot (cobot) arm grasps an object. Hardware components included a depth camera, cobot arm, and artificial intelligence equipment for edge computing. Software components included computer visualization techniques, deep learning, and robot operating system. To complete the preliminary implementation of the system, the grasping operation of the robot arm was set to target a ball. This system implementation sheds light on how robot arms and deep learning techniques are applied to real-life problems. Experiments verified that the preliminary system implemented was able to correctly complete the ball-grasping operation and achieve the pragmatic goal.