{"title":"基于目标检测的远程操作自动虚拟导引可视化系统的开发","authors":"Kyunghwan Cho, K. Ko, Heereen Shim, Inhoon Jang","doi":"10.1109/URAI.2018.8441808","DOIUrl":null,"url":null,"abstract":"This paper proposes automatically generate a virtual guidance for teleoperation system using object detection. A virtual guidance that gives force feedback when performing a mission like a peg-in-hole using a slave robot with a haptic device is very helpful for the operator. The key point of our study is to automatically generate this virtual guidance using deep learning architecture. If the operator uses this information, there is no need to generate a virtual guidance one by one. In addition, our system can automatically and continuously generate virtual guidance in moving situations as well as stationary situations. The position of the target object is recognized using deep learning architecture and depth information. And visual information of the virtual guidance is visualized using the virtual environment visualization system. Our system helps the operator to recognize spatial information.","PeriodicalId":347727,"journal":{"name":"2018 15th International Conference on Ubiquitous Robots (UR)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Development of Automatic Virtual Guidance Visualization System for Teleoperation Using Object Detection\",\"authors\":\"Kyunghwan Cho, K. Ko, Heereen Shim, Inhoon Jang\",\"doi\":\"10.1109/URAI.2018.8441808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes automatically generate a virtual guidance for teleoperation system using object detection. A virtual guidance that gives force feedback when performing a mission like a peg-in-hole using a slave robot with a haptic device is very helpful for the operator. The key point of our study is to automatically generate this virtual guidance using deep learning architecture. If the operator uses this information, there is no need to generate a virtual guidance one by one. In addition, our system can automatically and continuously generate virtual guidance in moving situations as well as stationary situations. The position of the target object is recognized using deep learning architecture and depth information. And visual information of the virtual guidance is visualized using the virtual environment visualization system. Our system helps the operator to recognize spatial information.\",\"PeriodicalId\":347727,\"journal\":{\"name\":\"2018 15th International Conference on Ubiquitous Robots (UR)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th International Conference on Ubiquitous Robots (UR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2018.8441808\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Conference on Ubiquitous Robots (UR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2018.8441808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of Automatic Virtual Guidance Visualization System for Teleoperation Using Object Detection
This paper proposes automatically generate a virtual guidance for teleoperation system using object detection. A virtual guidance that gives force feedback when performing a mission like a peg-in-hole using a slave robot with a haptic device is very helpful for the operator. The key point of our study is to automatically generate this virtual guidance using deep learning architecture. If the operator uses this information, there is no need to generate a virtual guidance one by one. In addition, our system can automatically and continuously generate virtual guidance in moving situations as well as stationary situations. The position of the target object is recognized using deep learning architecture and depth information. And visual information of the virtual guidance is visualized using the virtual environment visualization system. Our system helps the operator to recognize spatial information.