Lingzi Xie, Darong Huang, Zhenyu Lu, Ning Wang, Chenguang Yang
{"title":"Handheld Device Design for Robotic Teleoperation based on Multi-Sensor Fusion","authors":"Lingzi Xie, Darong Huang, Zhenyu Lu, Ning Wang, Chenguang Yang","doi":"10.1109/ICM54990.2023.10102054","DOIUrl":null,"url":null,"abstract":"Precise leader-follower control is critical for teleop- eration. This paper designs and implements a low-cost leader device for unilateral teleoperation scenario. Monocular vision based on fiducial markers and MEMS Inertial Measurement Unit (IMU) are utilized to constitute the pose sensing system of the handheld device. To increase the positioning output frequency and deal with the motion blur of the fiducial markers, the IMU data and vision message are fused by an Error State Kalman Filter (ESKF). An assembly experiment was carried out to verify the effectiveness of the proposed device and the feasibility of the fusion algorithm.","PeriodicalId":416176,"journal":{"name":"2023 IEEE International Conference on Mechatronics (ICM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Mechatronics (ICM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM54990.2023.10102054","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
Precise leader-follower control is critical for teleop- eration. This paper designs and implements a low-cost leader device for unilateral teleoperation scenario. Monocular vision based on fiducial markers and MEMS Inertial Measurement Unit (IMU) are utilized to constitute the pose sensing system of the handheld device. To increase the positioning output frequency and deal with the motion blur of the fiducial markers, the IMU data and vision message are fused by an Error State Kalman Filter (ESKF). An assembly experiment was carried out to verify the effectiveness of the proposed device and the feasibility of the fusion algorithm.