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Illumination Adaptability Research for SLAM Applications in Real Scenes
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1.Wuxi Research Institute, Nanjing University of Information Science &2.Technology;3.School of Remote Sensing and Surveying Engineering, Nanjing University of Information Science and Technology;4.School of Internet of things engineering, Wuxi University, Wuxi Research Institute of Nanjing University of Information Engineering;5.School of Automation, Nanjing University of Information Science &6.School of Spatial Information and Surveying and Mapping Engineering, Anhui University of Science and Technology,

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U46

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    Abstract:

    In order to explore the illumination adaptability of environmental perception equipment in the application of SLAM algorithm, verification evaluation experiments of lidar and depth camera SLAM algorithms were carried out under different illumination intensities. Based on a four-wheel differential robot, equipped with a 16-line lidar and a depth camera, combined with the LOAM(Lidar Odometry And Mapping) and RTAB_MAP (Real-Time Appearance-Based Mapping) algorithms, the lighting adaptability of the device is analyzed and verified in light and dark environments respectively. The experimental results show that in a bright environment, the median errors of the Visual SLAM and LiDAR SLAM system deviations are 0.203m and 0.644m, respectively; in the dark environment, the deviations of the two are 0.282m and 0.683m, respectively; The positioning and mapping effect of the depth camera in both bright and dark environments is better than that of the lidar, and the depth camera is more adaptable.

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History
  • Received:May 06,2022
  • Revised:July 03,2022
  • Adopted:July 05,2022
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