Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220300218-8.doi: 10.11896/jsjkx.220300218

• Software & Interdiscipline • Previous Articles     Next Articles

Design of Indoor Mapping and Navigation System Based on Multi-sensor

LIU Jiawei, DU Xin, FAN Fangzhao, XIE Chengbi   

  1. School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:LIU Jiawei,born in 1997,postgraduate.His main research interests include robot navigation and control. DU Xin,born in 1976,Ph.D,associate professor.Her main research interests include robotics and artificial intelligence.

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Abstract: Aiming at the problems of low positioning accuracy and limited ability to describe the environment in the process of map building and navigation of mobile robot based on single sensor,a multi-sensor sensing map building and navigation system based on robot operating system is developed.Firstly,an omnidirectional four-wheel Mecanum mobile chassis is built.Secondly,the RTAB-MAP algorithm is analyzed,and based on this algorithm,the RGB-D camera,lidar and odometer information are fused to realize the simultaneous construction of two-dimensional and three-dimensional maps of indoor environm ent.Thirdly,the extended Kalman filter algorithm is proposed to fuse the odometer information generated by the encoder with IMU data to improve the estimation accuracy of pose.Finally,the traditional robot navigation framework is optimized according to the fused data,the design of autonomous navigation function is completed.The test results show that the system adopts the multi-sensor sensing scheme,which can complete the construction of two-dimensional and three-dimensional maps of the indoor scene at the same time,and improve the ability to describe the environment.By using the fused data of extended Kalman filter,the positioning accuracy of the robot is significantly improved and the accuracy of navigation is ensured.

Key words: ROS, RTAB-MAP algorithm, RGB-D camera, Lidar, Data fusion, Mapping, Navigation

CLC Number: 

  • TP242
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