{"title":"协作机器人导通式教学规划的零力矩控制","authors":"S. Canfield, J. Owens, Stephen G. Zuccaro","doi":"10.1115/detc2020-22510","DOIUrl":null,"url":null,"abstract":"\n Robots are commonly used for automated welding in many industries such as automotive manufacturing. The complexity and time of programming presents an obstacle in using robotic automation in welding or other tasks for small to medium enterprises that lack resources for training or expertise in traditional robot programming strategies. It also dictates a high level of repeated parts to offset the cost of weld programming. Collaborative Robots or Cobots are robots designed for more collaborative operations with humans. Cobots permit new methods of task instruction (programming) through direct interaction between the operator and robot. This paper presents a model and calibration strategy for a collaborative robot to aid intuitive teaching methods for tasks such as welding. The method makes use of a torque estimation model based on robot momentum to create an observer to evaluate external forces. The torque observer is first used to characterize the friction that exists within the robot joints. This data is used to define the parameters of a friction model that combines static, Coulomb and viscous friction properties with a sigmoid function to represent transition between motion states and a second level Fourier series to represent position dependency of the Coulomb friction terms. The friction model is then integrated into the robot control and used to provide a mode in which the robot can be easily dragged around the workspace to provide weld path training.","PeriodicalId":365283,"journal":{"name":"Volume 10: 44th Mechanisms and Robotics Conference (MR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Zero Moment Control for Lead-Through Teach Programming on a Collaborative Robot\",\"authors\":\"S. Canfield, J. Owens, Stephen G. Zuccaro\",\"doi\":\"10.1115/detc2020-22510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Robots are commonly used for automated welding in many industries such as automotive manufacturing. The complexity and time of programming presents an obstacle in using robotic automation in welding or other tasks for small to medium enterprises that lack resources for training or expertise in traditional robot programming strategies. It also dictates a high level of repeated parts to offset the cost of weld programming. Collaborative Robots or Cobots are robots designed for more collaborative operations with humans. Cobots permit new methods of task instruction (programming) through direct interaction between the operator and robot. This paper presents a model and calibration strategy for a collaborative robot to aid intuitive teaching methods for tasks such as welding. The method makes use of a torque estimation model based on robot momentum to create an observer to evaluate external forces. The torque observer is first used to characterize the friction that exists within the robot joints. This data is used to define the parameters of a friction model that combines static, Coulomb and viscous friction properties with a sigmoid function to represent transition between motion states and a second level Fourier series to represent position dependency of the Coulomb friction terms. The friction model is then integrated into the robot control and used to provide a mode in which the robot can be easily dragged around the workspace to provide weld path training.\",\"PeriodicalId\":365283,\"journal\":{\"name\":\"Volume 10: 44th Mechanisms and Robotics Conference (MR)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 10: 44th Mechanisms and Robotics Conference (MR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/detc2020-22510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 10: 44th Mechanisms and Robotics Conference (MR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2020-22510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Zero Moment Control for Lead-Through Teach Programming on a Collaborative Robot
Robots are commonly used for automated welding in many industries such as automotive manufacturing. The complexity and time of programming presents an obstacle in using robotic automation in welding or other tasks for small to medium enterprises that lack resources for training or expertise in traditional robot programming strategies. It also dictates a high level of repeated parts to offset the cost of weld programming. Collaborative Robots or Cobots are robots designed for more collaborative operations with humans. Cobots permit new methods of task instruction (programming) through direct interaction between the operator and robot. This paper presents a model and calibration strategy for a collaborative robot to aid intuitive teaching methods for tasks such as welding. The method makes use of a torque estimation model based on robot momentum to create an observer to evaluate external forces. The torque observer is first used to characterize the friction that exists within the robot joints. This data is used to define the parameters of a friction model that combines static, Coulomb and viscous friction properties with a sigmoid function to represent transition between motion states and a second level Fourier series to represent position dependency of the Coulomb friction terms. The friction model is then integrated into the robot control and used to provide a mode in which the robot can be easily dragged around the workspace to provide weld path training.