{"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}
引用次数: 4
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.