{"title":"Control Method for The Balance Recovery of Indirect Tight Coordination Task Based on Force Sensor","authors":"Mantian Li, Ran Guo, F. Zha, Fei Chen, Jian Huang","doi":"10.1109/ARSO.2018.8625720","DOIUrl":null,"url":null,"abstract":"In view of the problem of instability of movable objects due to disturbances in indirect tight coordination tasks (ITCT), a set of control methods were proposed. The movable objects can be controlled to return to initial position and maintain dynamic balance with these methods. These methods are based on two six-axis force/torque sensors, which are helpful to determine the position and velocity information of the movable object. With these information, the trajectory of the arms would be generated by the balance recovery controller to indirectly control the acceleration of the movable objects. By planning the acceleration reasonably, the movable objects can eventually return to initial position and keep dynamic balance. Finally, the validity and feasibility of this algorithm are verified by simulation.","PeriodicalId":441318,"journal":{"name":"2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARSO.2018.8625720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In view of the problem of instability of movable objects due to disturbances in indirect tight coordination tasks (ITCT), a set of control methods were proposed. The movable objects can be controlled to return to initial position and maintain dynamic balance with these methods. These methods are based on two six-axis force/torque sensors, which are helpful to determine the position and velocity information of the movable object. With these information, the trajectory of the arms would be generated by the balance recovery controller to indirectly control the acceleration of the movable objects. By planning the acceleration reasonably, the movable objects can eventually return to initial position and keep dynamic balance. Finally, the validity and feasibility of this algorithm are verified by simulation.