面向实际场景SLAM应用的光照适应性研究
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1.南京信息工程大学无锡研究院;2.南京信息工程大学遥感与测绘学院;3.无锡学院物联网工程学院,南京信息工程大学无锡研究院;4.南京信息工程大学自动化学院;5.安徽理工大学空间信息与测绘工程学院

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U46

基金项目:

2020年无锡市科技发展资金(N20201011);第十六批次江苏省“六大人才商峰”高层次人才项目(XYDXX-045);江苏省自然科学基金面上项目(BK20211037)。


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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    摘要:

    为探究不同SLAM算法在实际应用场景的光照适应性问题,在不同光照强度下进行基于激光雷达的激光SLAM和基于深度相机的视觉SLAM算法光照适应性评估实验。基于四轮差速机器人,搭载16线激光雷达和深度相机,结合LOAM(Lidar Odometry And Mapping)和RTAB_MAP(Real-Time Appearance-Based Mapping)算法,分别在明暗环境中分析验证SLAM系统的光照适应性。实验结果表明,在明亮环境下,基于视觉SLAM和激光SLAM系统偏差的中误差分别为0.203m,0.644m;在黑暗环境中两者偏差的中误差分别为±0.282m,±0.683m;深度相机在明、暗环境中的定位建图效果均优于激光雷达,深度相机的光照适应性更强。

    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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柯福阳,陆佳嘉,杭琦琳,宋宝.面向实际场景SLAM应用的光照适应性研究[J].南京信息工程大学学报,,():

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  • 收稿日期:2022-05-06
  • 最后修改日期:2022-07-03
  • 录用日期:2022-07-05
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