面向实际场景SLAM应用的光照适应性研究
DOI:
作者:
作者单位:

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

作者简介:

通讯作者:

中图分类号:

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
Author:
Affiliation:

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,

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    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.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2022-05-06
  • 最后修改日期:2022-07-03
  • 录用日期:2022-07-05
  • 在线发布日期:
  • 出版日期:

地址:江苏南京,宁六路219号,南京信息工程大学    邮编:210044

联系电话:025-58731025    E-mail:nxdxb@nuist.edu.cn

南京信息工程大学学报 ® 2022 版权所有  技术支持:北京勤云科技发展有限公司