{"title":"多无线运动捕捉节点的时间漂移补偿方法","authors":"Zeyang Dai, Chenghong Lu, Lei Jing","doi":"10.1109/HSI49210.2020.9142648","DOIUrl":null,"url":null,"abstract":"As we known, time synchronization is a crucial component of wireless sensor networks (WSNs), especially when performing the operation such as data fusion. In this paper, we revisit this problem for our proposed wireless motion capture (MoCap) nodes, namely WonderSense (WS), and present an easy and economical way to compensate time drift. We first explain the work principles of the proposed nodes. This part includes the overview of the device, and the approach to compensate the time drift for the built MoCap system. Then, the extended Kalman filter (EKF) for attitude estimation is implemented and briefly described. At last, several experiments are conducted to verify the feasibility of the time drift compensation method and validate the time drift compensated MoCap system during human walking. Results indicate that, on one hand, the proposed time drift compensation method is feasible, on the other hand, it is proved that the time drift compensated MoCap system is viable and reliable.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Time Drift Compensation Method on Multiple Wireless Motion Capture Nodes\",\"authors\":\"Zeyang Dai, Chenghong Lu, Lei Jing\",\"doi\":\"10.1109/HSI49210.2020.9142648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As we known, time synchronization is a crucial component of wireless sensor networks (WSNs), especially when performing the operation such as data fusion. In this paper, we revisit this problem for our proposed wireless motion capture (MoCap) nodes, namely WonderSense (WS), and present an easy and economical way to compensate time drift. We first explain the work principles of the proposed nodes. This part includes the overview of the device, and the approach to compensate the time drift for the built MoCap system. Then, the extended Kalman filter (EKF) for attitude estimation is implemented and briefly described. At last, several experiments are conducted to verify the feasibility of the time drift compensation method and validate the time drift compensated MoCap system during human walking. Results indicate that, on one hand, the proposed time drift compensation method is feasible, on the other hand, it is proved that the time drift compensated MoCap system is viable and reliable.\",\"PeriodicalId\":371828,\"journal\":{\"name\":\"2020 13th International Conference on Human System Interaction (HSI)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 13th International Conference on Human System Interaction (HSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HSI49210.2020.9142648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Conference on Human System Interaction (HSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HSI49210.2020.9142648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time Drift Compensation Method on Multiple Wireless Motion Capture Nodes
As we known, time synchronization is a crucial component of wireless sensor networks (WSNs), especially when performing the operation such as data fusion. In this paper, we revisit this problem for our proposed wireless motion capture (MoCap) nodes, namely WonderSense (WS), and present an easy and economical way to compensate time drift. We first explain the work principles of the proposed nodes. This part includes the overview of the device, and the approach to compensate the time drift for the built MoCap system. Then, the extended Kalman filter (EKF) for attitude estimation is implemented and briefly described. At last, several experiments are conducted to verify the feasibility of the time drift compensation method and validate the time drift compensated MoCap system during human walking. Results indicate that, on one hand, the proposed time drift compensation method is feasible, on the other hand, it is proved that the time drift compensated MoCap system is viable and reliable.