{"title":"Distributed formation control of a networked multi-robot system using estimation based event-trigger communication mechanism","authors":"Sayedhossein Mousavizadeh Kashipaz, A. M. Shahri","doi":"10.1109/ICRoM48714.2019.9071824","DOIUrl":null,"url":null,"abstract":"This paper concerns with distributed formation control problem of a multi-robot system subject to limited communication resources and unknown but bounded process measurement noise. In this paper, an estimation-based event-trigger communication scheme is proposed, which uses an estimator on each robot to obtain whether the current measurement should be transmitted. Because of nonlinearity in robot models, non-Gaussian data transition and the ability to reduce the effects of process measurement noise, the extended Kalman filter is used as an estimator in this paper. The proposed event-triggered scheduling scheme provides a better communication rate than other existing ones. The formation is achieved in a distributed manner using estimated data on each robot which means the formation control strategy is not different from a time-based sampling technic.","PeriodicalId":191113,"journal":{"name":"2019 7th International Conference on Robotics and Mechatronics (ICRoM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Conference on Robotics and Mechatronics (ICRoM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRoM48714.2019.9071824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper concerns with distributed formation control problem of a multi-robot system subject to limited communication resources and unknown but bounded process measurement noise. In this paper, an estimation-based event-trigger communication scheme is proposed, which uses an estimator on each robot to obtain whether the current measurement should be transmitted. Because of nonlinearity in robot models, non-Gaussian data transition and the ability to reduce the effects of process measurement noise, the extended Kalman filter is used as an estimator in this paper. The proposed event-triggered scheduling scheme provides a better communication rate than other existing ones. The formation is achieved in a distributed manner using estimated data on each robot which means the formation control strategy is not different from a time-based sampling technic.