{"title":"基于实时目标检测的Turtlebot 3室内定位与导航仿真","authors":"Chandran Nandkumar, Pranshu Shukla, Viren Varma","doi":"10.1109/CENTCON52345.2021.9687937","DOIUrl":null,"url":null,"abstract":"This paper proposes a method for indoor localization and navigation of Turtlebot 3 using Real Time Object Detection (RTOD). The robot is capable of recognizing the room it is placed inside based on the knowledge of positions of certain fixed arbitrary objects. The robot then proceeds to understand its position inside the room and is capable of moving to other locations. The robot is simulated using the ROS and Gazebo framework. The RTOD is trained to identify certain distinct objects like a rover, bowl, quadcopter and wheel based on which the robot is able to ascertain its location.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Simulation of Indoor Localization and Navigation of Turtlebot 3 using Real Time Object Detection\",\"authors\":\"Chandran Nandkumar, Pranshu Shukla, Viren Varma\",\"doi\":\"10.1109/CENTCON52345.2021.9687937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a method for indoor localization and navigation of Turtlebot 3 using Real Time Object Detection (RTOD). The robot is capable of recognizing the room it is placed inside based on the knowledge of positions of certain fixed arbitrary objects. The robot then proceeds to understand its position inside the room and is capable of moving to other locations. The robot is simulated using the ROS and Gazebo framework. The RTOD is trained to identify certain distinct objects like a rover, bowl, quadcopter and wheel based on which the robot is able to ascertain its location.\",\"PeriodicalId\":103865,\"journal\":{\"name\":\"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)\",\"volume\":\"148 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CENTCON52345.2021.9687937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CENTCON52345.2021.9687937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
提出了一种基于实时目标检测(Real Time Object Detection, RTOD)的Turtlebot 3室内定位与导航方法。机器人能够基于某些固定任意物体的位置知识来识别它所在的房间。然后，机器人继续了解自己在房间内的位置，并能够移动到其他位置。利用ROS和Gazebo框架对机器人进行仿真。RTOD经过训练，可以识别某些不同的物体，如漫游者、碗、四轴飞行器和轮子，机器人可以根据这些物体确定自己的位置。
Simulation of Indoor Localization and Navigation of Turtlebot 3 using Real Time Object Detection
This paper proposes a method for indoor localization and navigation of Turtlebot 3 using Real Time Object Detection (RTOD). The robot is capable of recognizing the room it is placed inside based on the knowledge of positions of certain fixed arbitrary objects. The robot then proceeds to understand its position inside the room and is capable of moving to other locations. The robot is simulated using the ROS and Gazebo framework. The RTOD is trained to identify certain distinct objects like a rover, bowl, quadcopter and wheel based on which the robot is able to ascertain its location.
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