LiDAR-SLAM-RES
Table of Contents
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
- 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
Books
Courses
Online Resources
Tutorials
Projects
Project I — Hardware Configuration: Laser and IMU Sensors
- IMU:
Project II — Laser-based SLAM (Part 1): Google Cartographer
- 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.- source(compressed): Google-Cartographer-Packages
- 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. - Correlative Scan Matching
Olson E B. Real-time correlative scan matching[C]//2009 IEEE International Conference on Robotics and Automation. IEEE, 2009: 4387-4393. - 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. - 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
- Castellanos, J.A., Neira, J., & Tardós, J.D. (2005). Map Building and SLAM Algorithms.
- 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.
- 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.
- Alexandersson, J., & Nordin, O. (2017). Implementation of SLAM algorithms in a small-scale vehicle using model-based development.
- Yagfarov, Rauf & Ivanou, Mikhail & Afanasyev, Ilya. (2018). Map Comparison of Lidar-based 2D SLAM Algorithms Using Precise Ground Truth. 10.1109/ICARCV.2018.8581131.
- Felipe Jiménez, Miguel Clavijo and Javier Juana. (VEHICULAR 2018). LiDAR-based SLAM algorithm for indoor scenarios.
- 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.
- 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.
- 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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