The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
권호 표지
DOI QR코드

DOI QR Code

Study on Extending Sensing Range of Fiducial Marker using Tilt Camera

틸트 카메라를 이용한 기준 마커 인식 범위 확장을 위한 연구

  • Received : 2022.10.24
  • Accepted : 2022.11.28
  • Published : 2023.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper studies the method to extend the sensing range of a fiducial maker using a tilt camera. In the system that uses a fiducial marker to estimate their position on a map, the sensing range of the marker is an important issue. Although there are markers around, a robot with a fixed camera often misses nearby markers in the case that the viewing angle of the camera does not cover the sensing range of the marker. If the robot adjusts the viewing angle of a camera by adjusting the position information of the markers, this problem will be solved. The contribution of this paper is as follows. 1) Structural considerations for the tilting module of cameras attached to robots. 2) Tilting module control method considering the position of a marker and a robot. 3) Finally, verification of the differences in the sensing range of markers between the proposed system and the previous system.

Keywords

Acknowledgement

This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry (IPET) through Smart Agri Products Flow Storage Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (322054-5)

References

  1. M. Betke and L. Gurvits, "Mobile Robot Localization using Landmarks," IEEE Transactions on Robotics and Automation, vol. 13, no. 2, pp. 251-263, Apr., 1997, DOI: 10.1109/70.563647.
  2. M. Kost'ak and A. Slaby, "Designing a Simple Fiducial Marker for Localization in Spatial Scenes Using Neural Networks," Sensors, vol. 21, no. 16, Aug., 2021, DOI: 10.3390/s21165407.
  3. G. Kang, D. Lee, and H. Shim, "3D Multi-floor Precision Mapping and Localization for Indoor Autonomous Robots," Journal of Korea Robotics Society, vol. 17, no. 1, pp. 25-31, Mar., 2022, DOI: 10.7746/jkros.2022.17.1.025.
  4. A, Babinec, L. Jurisica, P. Hubinsky, and F. Pchon, "Visual Localization of Mobile Robot using Artificial Markers," Procedia Engineering, vol. 96, pp. 1-9, 2014, DOI: 10.1016/j.proeng.2014.12.091.
  5. R. Yagfarov, M. Ivanou, and I. Afanasyev, "Map Comparison of Lidar-based 2D SLAM Algorithms using Precise Ground Truth," International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, 2018, DOI: 10.1109/ICARCV.2018.8581131.
  6. S. Petkovic, L. Milic, M. Nikolic, D. Miskovic, and M. Rakovic, "Comparison of SLAM Algorithms on Omnidirectional Four Wheel Mobile Robot," International Conference IcETRAN, Novi Pazar, Serbia, 2022, [Online], https://www.etran.rs/2022/zbornik/ICETRAN-22_radovi/082-ROI1.5.pdf.
  7. R. Negenborn, "Robot Localization and Kalman Filters," M.S thesis Utrecht Univ., Utrecht, Netherlands, 2003, [Online], http://www.negenborn.net/kal_loc/thesis.pdf.
  8. P. K. Panigrahi and S. K. Bisoy, "Localization Strategies for Autonomous Mobile Robots: A review," Journal of King Saud University-Computer and Information Sciences, vol. 34, no, 8, pp. 6019-6039, Sept., 2021, DOI: 10.1016/j.jksuci.2021.02.015.
  9. M. Fiala, "Designing Highly Reliable Fiducial Markers," IEEE Transactions on Pattern analysis and machine intelligence, vol. 32, no. 7, pp. 1317-1324, Jul., 2009, DOI: 10.1109/TPAMI.2009.146.
  10. W. Lee and W. Woo, "Rectangular Marker Recognition using Embedded Context Information," HCI 2009, [Online], https://koreascience.kr/article/CFKO200925752343977.pdf.
  11. F. J. Romero-Ramire, R. Munoz-Salinas, and R. Medina-Carnicer, "Fractal Markers: A New Approach for Long-range Marker Pose Estimation under Occlusion," IEEE Access, vol. 7, pp. 169908- 169919, Nov., 2019, DOI: 10.1109/ACCESS.2019.2951204.
  12. J. Ahn, S. Shin, and J. Park, "Development of Localization using Artificial and Natural Landmark for Indoor Mobile Robots," Journal of Korea Robotics Society, vol. 11, no. 4, pp. 205-216, Jul., 2016, DOI: 10.7746/jkros.2016.11.4.205.
  13. D.-G. Gwak, K.-M. Yang, M.-R. Park, J. Hahm, J. Koo, J. Lee, and K.-H. Seo, "Marker-Based Method for Recognition of Camera Position for Mobile Robots," Sensors, vol. 21, no. 4, Feb., 2021, DOI: 10.3390/s21041077.
  14. H. Liu, N. Stoll, S. Junginger, and K. Thurow, "New Localization Strategy for Mobile Robot Transportation in Life Science Automation using StarGazer Sensor, Time series Modeling and Kalman Filter Processing," IEEE International Conference on Robotics and Biomimetics, Zhuhai, China, 2015, DOI: 10.1109/ROBIO.2015.7418761.
  15. L. Joseph, ROS Robotics projects, 2nd ed. Packt Publishing Ltd, 2017, [Online], https://www.packtpub.com/product/ros-roboticsprojects/9781783554713.
  16. cartographer-project/cartographer, [Online], https://github.com/cartographer-project/cartographer, Accessed: Jan. 26, 2023.