JRM Vol.31 No.2 pp. 194-202
doi: 10.20965/jrm.2019.p0194


Robust Human Tracking of a Crawler Robot

Yasuaki Orita and Takanori Fukao

Graduate School of Science and Engineering, Ritsumeikan University
1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan

October 22, 2018
January 28, 2019
April 20, 2019
human tracking, automatic tracking, 3D-LiDAR, NDT-SLAM, inverse optimal control

Carrying out firefighting activities at disaster sites is extremely difficult. Therefore, robots that support and enhance these operations are required. In this paper, a crawler robot that tracks the moving path of a firefighter is proposed. It is commonly believed that trained firefighters select the best route; thus, it was assumed that this route is the easiest for the crawler robot as well. Using two 3D light detection and ranging sensors, once the firefighter’s coordinates are detected, the coordinates are combined with 3D simultaneous localization and mapping results, then a target path is generated. The crawler robot follows the path using inverse optimal tracking control. The controller has a stability margin that guarantees robustness, which is an ideal property for disaster response robots used in severe conditions. The results of several experiments show that the proposed system is effective and practical for the crawler robot.

A crawler robot tracks a person automatically

A crawler robot tracks a person automatically

Cite this article as:
Y. Orita and T. Fukao, “Robust Human Tracking of a Crawler Robot,” J. Robot. Mechatron., Vol.31 No.2, pp. 194-202, 2019.
Data files:
  1. [1] R. R. Murphy, “Disaster Robotics,” MIT Press, 2014.
  2. [2] M. K. Habib and Y. Baudoin, “Robot-Assisted Risky Intervention, Search, Rescue and Environmental Surveillance,” Int. J. of Advanced Robotic System, Vol.7, No.1, pp. 1-8, 2010.
  3. [3] K. Tokuda, T. Hirayama, T. Kinugawa, T. Haji, H. Amano, and K. Yasuda, “Complement Method for Obstructed Area on Images of Multiple Cameras Mounted Behind Crawler Shoe,” J. Robot. Mechatron., Vol.27, No.2, pp. 146-155, 2015.
  4. [4] H. Amano, “Needs for Disaster Response Robots,” J. of the Robotics Society of Japan, Vol.27, No.3, pp. 287-290, 2009 (in Japanese).
  5. [5] Y. Okada, K. Nagatani, and K. Yoshida, “Semi-autonomous operation of Tracked Vehicles on Rough Terrain using Autonomous Control of Active Flippers,” Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 2815-2820, 2009.
  6. [6] M. Kamezaki, J. Yang, H. Iwata, and S. Sugano, “A Basic Framework of virtual Reality Simulator for Advancing Disaster Response Work Using Teleoperated Work Machines,” J. Robot. Mechatron., Vol.26, No.4, pp. 486-495, 2014.
  7. [7] M. Wang, D. Su, L. Shi, Y. Liu, and J. V. Miro, “Real-time 3D Human Tracking for Mobile Robots with Multisensors,” Proc. IEEE Int. Conf. Robotics and Automation, pp. 5081-5087, 2017.
  8. [8] N. Bellotto and H. Hu, “Multisensor-based human detection and tracking for mobile service robots,” IEEE Trans. Systems, Man, and Cybernetics, Part B (Cybernetics), Vol.39, No.1, pp. 167-181, 2009.
  9. [9] E.-J. Jung, J. H. Lee, B.-J. Yi, J. Park, S. Yuta, and S.-T. Noh, “Development of a Laser-Range-Finder-Based Human Tracking and Control Algorithm for a Marathoner Service Robot,” IEEE/ASME Trans. Mechatronics, Vol.19, No.6, pp. 1963-1976, 2014.
  10. [10] W. Hess, D. Kohler, H. Rapp, and D. Andor, “Real-Time Loop Closure in 2D LiDAR SLAM,” Proc. IEEE Int. Conf. Robotics and Automation, pp. 1271-1278, 2016.
  11. [11] G. Grisetti, C. Stachniss, and W. Burgard, “Improve Techniques for Grid Mapping with Rao-Blackwellized Particle Filters,” IEEE Trans. Robotics, Vol.23, No.1, pp. 33-46, 2007.
  12. [12] Y. Iwano, K. Osuka, and H. Amano, “Development of Human following System Using FRIGO – the 2nd report – Improvement of stability and safety,” 11th Proc. of the System Integration Division (SI2010), pp. 1324-1326, 2010 (in Japanese).
  13. [13] S. Nakamura, T. Hasegawa, T. Hiraoka, Y. Ochiai, and S. Yuta, “Person Searching Through an Omnidirectional Camera Using CNN in the Tsukuba Challenge,” J. Robot. Mechatron., Vol.30, No.4, pp. 540-551, 2018.
  14. [14] T. Fukao, “Inverse Optimal Tracking Control of a Nonholonomic Mobile Robot,” Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 1475-1480, 2004.
  15. [15] P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.14, No.2, pp. 239-256, 1992.
  16. [16] D. Aiger, N. J. Mitra, and D. Cohen-Or, “4-points congruent sets for robust pairwise surface registration,” ACM Trans. on Graphics, Vol.27, No.3, pp. 1-10, 2008.
  17. [17] P. Biber and W. Strasser, “The normal distributions transform: A new approach to laser scan matching,” Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 2743-2748, 2003.
  18. [18] B. Huhle, M. Magnusson, W. Strasser, and A. Lilienthal, “Registration of Colored 3D Point Clouds with a Kernel-based Extension to the Normal Distributions Transform,” Proc. IEEE Int. Conf. Robotics and Automation, pp. 4025-4030, 2008.
  19. [19] M. Magnusson, A. Lilienthal, and T. Duckett, “Scan Registration for Autonomous Mining Vehicles Using 3D-NDT,” J. of Field Robotics, Vol.24, No.10, pp. 803-827, 2007.
  20. [20] E. D. Sontag, “Mathematical Control Theory,” Springer, 1998.
  21. [21] R. Sepulchre, M. Jankovic, and P. Kokotovic, “Constructive Nonlinear Control,” Prentice Hall, 1996.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jun. 03, 2024