Yuki Ayuta, Kouhei Okuda, Eisuke Kawamoto, S. Muramatsu, K. Inagaki, D. Chugo, Syo Yokota, H. Hashimoto
{"title":"Study on forestry control system to improve forestry workers safety","authors":"Yuki Ayuta, Kouhei Okuda, Eisuke Kawamoto, S. Muramatsu, K. Inagaki, D. Chugo, Syo Yokota, H. Hashimoto","doi":"10.1109/IECON48115.2021.9589835","DOIUrl":null,"url":null,"abstract":"In this paper, we describe the integrated system for ensuring the safety of forestry workers. It is difficult to accurately acquire GPS information in forests. Therefore, it is necessary to consider a position estimation method that does not use GPS. First, the accuracy of VisualSLAM, IMU, and Beacon alone was verified and evaluated by experiments. We also examined the communication method and self-position estimation system for the integrated system. The results show that the self-positioning of Visual SLAM and IMU requires a large interval for correction, which results in a large error. Therefore, we found that the larger the measurement interval, the larger the error of any sensor system. The future tasks are to improve the accuracy of sensor systems, to optimize the measurement interval, and to integrate the systems.","PeriodicalId":443337,"journal":{"name":"IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON48115.2021.9589835","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
In this paper, we describe the integrated system for ensuring the safety of forestry workers. It is difficult to accurately acquire GPS information in forests. Therefore, it is necessary to consider a position estimation method that does not use GPS. First, the accuracy of VisualSLAM, IMU, and Beacon alone was verified and evaluated by experiments. We also examined the communication method and self-position estimation system for the integrated system. The results show that the self-positioning of Visual SLAM and IMU requires a large interval for correction, which results in a large error. Therefore, we found that the larger the measurement interval, the larger the error of any sensor system. The future tasks are to improve the accuracy of sensor systems, to optimize the measurement interval, and to integrate the systems.