single-rb.php

JRM Vol.33 No.3 pp. 610-617
doi: 10.20965/jrm.2021.p0610
(2021)

Development Report:

FST-Convoy: A Leader Tracking Control of Vehicles Connected by Shape Sensor FST

Daisuke Ura, Kotaro Masumoto, and Koichi Osuka

Osaka University
Central Terrace 5F, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan

Received:
October 6, 2020
Accepted:
March 3, 2021
Published:
June 20, 2021
Keywords:
flexible sensor tube, platooning, construction machine, following driving, mobile robot
Abstract

This paper describes FST-Convoy, a leader tracking control system for vehicles using the shape sensor flexible sensor tube (FST). Among many methods of autonomous driving, follow-driving is one of them. Some of these have been put into practical use in a limited environment. Unfortunately, there are situations in which such sensors do not work well. One of these is underground. In the underground, GNSS signals do not reach vehicles, so they cannot obtain their positions. Therefore, we propose a new way to achieve follow-driving in such environments. We used the shape sensor, FST. The FST is a shape sensor with a serial link structure and many joints. It can measure its shape by solving its kinematics and determine the relative position of the start link to the end link. Therefore, we can measure the relative positions of vehicles that connected a leader and a follower using FST. We call this system FST-Convoy. We developed and verified the system using a platooning-driving experiment.

FST-Convoy: vehicles connected by FST

FST-Convoy: vehicles connected by FST

Cite this article as:
D. Ura, K. Masumoto, and K. Osuka, “FST-Convoy: A Leader Tracking Control of Vehicles Connected by Shape Sensor FST,” J. Robot. Mechatron., Vol.33 No.3, pp. 610-617, 2021.
Data files:
References
  1. [1] Z. Horii, “Development of offroad unmanned dump truck navigation system,” Shigen-to-Sozai, Vol.108, No.8, pp. 575-578, 1992.
  2. [2] S. Scheding, G. Dissanayake, E. M. Nebot, and H. Durrant-Whyte, “An experiment in autonomous navigation of an underground mining vehicle,” IEEE Trans. on Robotics and Automation, Vol.15, No.1, pp. 85-95, 1999.
  3. [3] J. Li, H. Bao, F. Pan, F. Zhang, and D. Wang, “Real-time self-driving car navigation and obstacle avoidance using mobile 3D laser scanner and GNSS,” Multimed. Tools Appl., Vol.76, pp. 23017-23039, 2017.
  4. [4] H. Cho, Y. Seo, B. V. K. V. Kumar, and R. R. Rajkumar, “A multi-sensor fusion system for moving object detection and tracking in urban driving environments,” 2014 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 1836-1843, 2014.
  5. [5] U. Lee, J. Jung, S. Jung, and D. H. Shim, “Development of a self-driving car that can handle the adverse weather,” Int. J. of Automotive Technology, Vol.19, pp. 191-197, 2018.
  6. [6] C. J. Ostafew, A. P. Schoellig, and T. D. Barfoot, “Visual teach and repeat, repeat, repeat: Iterative learning control to improve mobile robot path tracking in challenging outdoor environments,” 2013 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 176-181, 2013.
  7. [7] T. Fukao and K. Kurashiki, “Image-based robust arbitrary path following of nonholonomic mobile robots,” Trans. of the Society of Instrument and Control Engineers, Vol.47, No.5, pp. 238-246, 2011.
  8. [8] E. Royer, M. Lhuiller, M. Dhome, and J. Lavest, “Monocular vision for mobile robot localization and autonomous navigation,” Int. J. of Computer Vision, Vol.74, pp. 237-260, 2007.
  9. [9] G. H. Lee, F. Faundorfer, and M. Pollefeys, “Motion Estimation for Self-Driving Cars with a Generalized Camera,” The IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 2746-2753, 2013.
  10. [10] S. Hong, M. Li, and P. van Beek, “Real-time mobile robot navigation based on stereo vision and low-cost GPS,” J. of Electronic Imaging, pp. 10-15, 2017.
  11. [11] Z. Chen and S. T. Birchfield, “Qualitative vision-based mobile robot navigation,” Proc. 2006 IEEE Int. Conf. on Robotics and Automation, pp. 2686-2692, 2006.
  12. [12] K. Miyashita, S. Kawaji, and T. Ishii, “Development and operation of the autonomous mining truck system,” J. of MMIJ, Vol.125, No.10, pp. 509-513, 2009.
  13. [13] S. Dominguez, B. Khomutenko, G. Garcia, and P. Martinet, “An optimization technique for positioning multiple maps for self-driving car’s autonomous navigation,” 2015 IEEE 18th Int. Conf. on Intelligent Transportation Systems, pp. 2694-2699, 2015.
  14. [14] B. van Arem, C. J. G. van Driel, and R. Visser, “The impact of cooperative adaptive cruise control on traffic-flow characteristics,” IEEE Trans. on Intelligent Transportation Systems, Vol.7, No.4, pp. 429-436, 2006.
  15. [15] V. Milanés, S. E. Shladover, J. Spring, C. Nowakowski, H. Kawazoe, and M. Nakamura, “Cooperative adaptive cruise control in real traffic situations,” IEEE Trans. on Intelligent Transportation Systems, Vol.15, No.1, pp. 296-305, 2014.
  16. [16] R. Parker and S. Valaee, “Cooperative vehicle position estimation,” 2007 IEEE Int. Conf. on Communications, pp. 5837-5842, 2007.
  17. [17] G. Lu and M. Tomizuka, “Lidar sensing for vehicle lateral guidance: Algorithm and experimental study,” IEEE/ASME Trans. on Mechatronics, Vol.11, No.6, pp. 653-660, 2006.
  18. [18] S. Tsugawa, “An overview on an automated truck platoon within the energy its project,” IFAC Proc., Vol.46, pp. 41-46, 2013.
  19. [19] G. Lu and M. Tomizuka, “Vehicle lateral control with combined use of a laser scanning radar sensor and rear magnetometers,” Proc. of the 2002 American Control Conf., pp. 3702-3707, 2002.
  20. [20] G. Endo, Y. Iemura, E. F. Fukushima, M. Iribe, and M. Ohira, “Mobile follower robot as an assistive device for home oxygen therapy – evaluation of tether control algorithms,” ROBOMECH J., Vol.2, 6, 2015.
  21. [21] K. Osuka, R. Haraguchi, J. Masukawa, T. Wada, Y. Kitada, and K. Kusunoki, “Development of Flexible Sensor Tube: FST,” SICE System Integration Division Annual Conf., pp. 327-328, 2005.
  22. [22] K. Maeda and K. Osuka, “Error analysis of FST for accuracy improvement,” Proc. of SICE Annual Conf. 2010, pp. 1698-1700, 2010.
  23. [23] K. Osuka and T. Iwata, “Master-slave Control of Dual Manipulator with FST,” Proc. of JSME Annual Conf. on Robotics and Mechatronics, 2P1-J06, 2007.
  24. [24] K. Osuka, Y. Iwano, and H. Amano, “Human Following Mobile Robot FRIGO Using Flexible Sensor Tube,” SICE System Integration Division Annual Conf., pp. 278-279, 2007.

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

Last updated on Nov. 04, 2024