Tuesday, August 4, 2020

LiDAR SLAM Navigatio Resources



A page of LiDAR SLAM Navigatio Resources (LiDAR-SLAM-Nav-RES) to follow up current LiDAR SLAM based Navigation trends, including key papers, books, engineering projects, as well as valuable blogs.

(Current) Project III — Motion Planning

ROS Research Papers

  • ROS Layered Costmaps
David V. Lu, D. Hershberger and W. D. Smart, "Layered costmaps for context-sensitive navigation," 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, 2014, pp. 709-715. pdf
  • Layered Social Cost Map
  • Kollmitz, Marina, et al. "Time Dependent Planning on a Layered Social Cost Map for Human-Aware Robot Navigation." 2015 European Conference on Mobile Robots (ECMR). IEEE, 2015. pdf
  • (2019/07/19) David V. Lu, Daniel B. Allan, and William D. Smart. "Tuning Cost Functions for Social Navigation." International Conference on Social Robotics. Springer, Cham, 2013. pdf
  • ROS Navigation Tuning Guide
Kaiyu Zheng, ROS Navigation Tuning Guide. arXiv preprint arXiv:1706.09068v2, Sep. 2016. pdf
  • ROS Navigation: Concepts and Tutorial
Guimarães R L, de Oliveira A S, Fabro J A, et al. ROS navigation: Concepts and tutorial[M]//Robot Operating System (ROS). Springer, Cham, 2016: 121-160. pdf
  • Robotics Engineering 2: ROS-Turtlebot Motion Control and Navigation
AK Assad, Mashruf Chowdhury, and Yanik Porto, Robotics Engineering 2: ROS-Turtlebot Motion Control and Navigation. May 11, 2015. pdf


  • Robotics (Release 1.4)
Jeff McGough, Book title: Robotics. Date: Dec./02/2018. pdf
  • 《机器人操作系统(ROS)史话36 篇》
张新宇, pdf
  • 《人类找北史:从罗盘到GPS,导航定位的过去与未来》
Bray, Hiawatha. You are here: From the compass to GPS, the history and future of how we find ourselves. Basic Books (AZ), 2014. pdf(中文翻译)


  • 《智能机器人系统》
国防科技大学智能科学学院, 卢惠民,郑志强,韦庆,肖军浩,杨绍武,曾志文, link
  • 《机器人操作系统入门》(2018)
中科院软件所&中科重德机器人公司, 柴长坤, link

Online Resources


  • 机器人操作系统(ROS)暑期学校, type: video&pdf, link
  • 专栏文章:ROS激光SLAM导航(`move_base`参数配置注释), type: blog, link
  • 小强ROS机器人教程, type: pdf, link
  • 机器人操作系统(ROS)浅析, type:pdf, link
  • ROS小课堂, type:blog, link
  • Exbot 易科实验室, link


  1. PythonRobotics
  2. ROS Navigation Stack


1) 硬件平台

2) AGV 国家标准

  • 《GB/T 30029 自动导引车(AGV) 设计通则》, pdfpdf(candidate )
  • 《GB/T 30030 自动导引车(AGV) 术语》, pdfpdf(candidate )
  • 《GB/T 20721 自动导引车 通用技术条件》, pdf

Project I — Hardware Configuration: Laser and IMU Sensors

  1. Laser: Osight LSXXXTM laser sensor configuration & test:
  2. IMU:

Project II — Laser-based SLAM (Part 1): Google Cartographer

  1. Google Cartographer
    Hess W, Kohler D, Rapp H, et al. Real-time loop closure in 2D LIDAR SLAM [C]//2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016: 1271-1278.
  1. Sparse Pose Adjustment (SPA)
    Konolige K, Grisetti G, Kümmerle R, et al. Efficient sparse pose adjustment for 2D mapping[C]//2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2010: 22-29.
  2. Correlative Scan Matching
    Olson E B. Real-time correlative scan matching[C]//2009 IEEE International Conference on Robotics and Automation. IEEE, 2009: 4387-4393.
  3. Ceres Scan Matching
    Kohlbrecher S, Von Stryk O, Meyer J, et al. A flexible and scalable slam system with full 3d motion estimation[C]//2011 IEEE International Symposium on Safety, Security, and Rescue Robotics. IEEE, 2011: 155-160.
  4. Branch and Bound Algorithm
    Clausen J. Branch and bound algorithms-principles and examples[J]. Department of Computer Science, University of Copenhagen, 1999: 1-30.

Project II — Laser-based SLAM (Part 2): LiDAR SLAM Survey

  1. Castellanos, J.A., Neira, J., & Tardós, J.D. (2005). Map Building and SLAM Algorithms.
  2. Santos, J. M., Portugal, D., & Rocha, R. P. (2013, October). An evaluation of 2D SLAM techniques available in robot operating system. In 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) (pp. 1-6). IEEE.
  3. Mendes, E., Koch, P., & Lacroix, S. (2016, October). ICP-based pose-graph SLAM. In 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) (pp. 195-200). IEEE.
  4. Yagfarov, Rauf & Ivanou, Mikhail & Afanasyev, Ilya. (2018). Map Comparison of Lidar-based 2D SLAM Algorithms Using Precise Ground Truth. 10.1109/ICARCV.2018.8581131.
  5. Felipe Jiménez, Miguel Clavijo and Javier Juana. (VEHICULAR 2018). LiDAR-based SLAM algorithm for indoor scenarios.
  6. Yagfarov, R., Ivanou, M., & Afanasyev, I. (2018, November). Map Comparison of Lidar-based 2D SLAM Algorithms Using Precise Ground Truth. In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) (pp. 1979-1983). IEEE.
  7. Kümmerle, R., Steder, B., Dornhege, C., Ruhnke, M., Grisetti, G., Stachniss, C., & Kleiner, A. (2009). On measuring the accuracy of SLAM algorithms. Autonomous Robots, 27(4), 387.
  8. Chen, Y., Tang, J., Jiang, C., Zhu, L., Lehtomäki, M., Kaartinen, H., …​ & Zhou, H. (2018). The accuracy comparison of three simultaneous localization and mapping (SLAM)-Based indoor mapping technologies. Sensors, 18(10), 3228.

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