The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Loosely Coupled LiDAR-visual Mapping and Navigation of AMR in Logistic Environments

실내 물류 환경에서 라이다-카메라 약결합 기반 맵핑 및 위치인식과 네비게이션 방법

  • Choi, Byunghee (Department of Robotics Engineering, YeungNam University) ;
  • Kang, Gyeongsu (Department of Robotics Engineering, YeungNam University) ;
  • Roh, Yejin (Department of Robotics Engineering, YeungNam University) ;
  • Cho, Younggun (Department of Electrical Engineering, Inha University)
  • Received : 2022.09.03
  • Accepted : 2022.10.06
  • Published : 2022.11.30
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Abstract

This paper presents an autonomous mobile robot (AMR) system and operation algorithms for logistic and factory facilities without magnet-lines installation. Unlike widely used AMR systems, we propose an EKF-based loosely coupled fusion of LiDAR measurements and visual markers. Our method first constructs occupancy grid and visual marker map in the mapping process and utilizes prebuilt maps for precise localization. Also, we developed a waypoint-based navigation pipeline for robust autonomous operation in unconstrained environments. The proposed system estimates the robot pose using by updating the state with the fusion of visual marker and LiDAR measurements. Finally, we tested the proposed method in indoor environments and existing factory facilities for evaluation. In experimental results, this paper represents the performance of our system compared to the well-known LiDAR-based localization and navigation system.

Keywords

Acknowledgement

This project was funded by Inha University and YJLink. Also, this work was supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0017124) and nstitute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2022-0-00448) and Korea Institute of Marine Science and Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries (20210562)

References

  1. MiR Robotics, [Online], https://www.mobile-industrial-robots.com, Accessed: September 16, 2022.
  2. C. Debeunne and D. Vivet, "A review of visual-LiDAR fusion based simultaneous localization and mapping," Sensors, vol. 20, no. 7, 2020, DOI: 10.3390/s20072068.
  3. G. Grisetti, C. Stachniss, and W. Burgard, "Improving gridbased SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling," 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 2432-2437, 2005, DOI: 10.1109/ROBOT.2005.1570477.
  4. W. Hess, D. Kohler, H. Rapp, and D. Andor, "Real-time loop closure in 2D LIDAR SLAM," 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, pp. 1271-1278, 2016, DOI: 10.1109/ICRA.2016.7487258.
  5. E. Pedrosa, A. Pereira, and N. Lau, "Efficient localization based on scan matching with a continuous likelihood field," 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Coimbra, Portugal, pp. 61-66, 2017, DOI: 10.1109/ICARSC.2017.7964053.
  6. S. Quinlan and O. Khatib, "Elastic bands: connecting path planning and control," [1993] Proceedings IEEE International Conference on Robotics and Automation, Atlanta, GA, USA, pp. 802-807, 1993, DOI: 10.1109/ROBOT.1993.291936.
  7. C. Rosmann, W. Feiten, T. Wosch, F. Hoffmann, and T. Bertram, "Trajectory modification considering dynamic constraints of autonomous," ROBOTIK 2012 robots, 2012, [Online], http://files.davidqiu.com/research/papers/2012_rosmann_TEB%Planner%Trajectory%modification%considering%dynamic%constraints%of%autonomous%robots%[ROBOTIK%2012].pdf, 2012.
  8. F. J. Romero-Ramirez, R. Munoz-Salinas, and R. Medina-Carnicer, "Speeded up detection of squared fiducial markers," Image and Vision Computing, vol. 76, pp. 38-47, 2018, DOI: 10.1016/j.imavis.2018.05.004.
  9. S. Yavuz, Z. Kurt, and M. S. Bicer, "Simulataneous localization and mapping with the extended Kalman filter," 2009 IEEE 17th Signal Processing and Communications Applications ConferenceSola, Antalya, Turkey, pp. 2009, DOI: 10.1109/SIU.2009.5136492.
  10. P. E. Hart, N. J. Nilsson, and B. Raphael, "A formal basis for the heuristic determination of minimum cost paths," IEEE Transactions on Systems Science and Cybernetics, vol. 4, no. 2, pp.100-107, July, 1968, DOI: 10.1109/TSSC.1968. 300136.
  11. K. Konstantinidis, "Development of a Detection and Tracking of Moving Vehicles system for 2D LIDAR sensors," M.S thesis, Delft University of Technology, The Netherlands, 2020, [Online], https://repository.tudelft.nl/islandora/object/uuid%3A103fe186-925e-46f7-8275-d746e7c47600.