single-rb.php

JRM Vol.25 No.2 pp. 400-407
doi: 10.20965/jrm.2013.p0400
(2013)

Paper:

Path Planning for Autonomous Vehicles Using QZSS and Satellite Visibility Map

Mitsunori Kitamura*, Yoichi Yasuoka*, Taro Suzuki**,
Yoshiharu Amano*, and Takumi Hashizume*

*Research Institute for Science and Engineering, Waseda University, 17 Kikui-cho, Shinjuku-ku, Tokyo 162-0044, Japan

**JSPS Research Fellow, Tokyo University of Marine Science and Technology, 2-1-6 Etchujima, Koto-ku, Tokyo 135-8533, Japan

Received:
October 19, 2012
Accepted:
February 20, 2013
Published:
April 20, 2013
Keywords:
QZSS, GPS, path planning, satellite visibility map
Abstract

This paper describes a path planning method that uses the Quasi-Zenith Satellites System(QZSS) and a satellite visibility map for autonomous vehicles. QZSS is a positioning system operated by Japan that has an effect similar to an increase in the number of GPS satellites. Therefore, QZSS can be used to improve the availability of GPS positioning. A satellite visibility map is a special map that simulates the number of visible satellites at all points on the map. The vehicle can use the satellite visibility map to determine the points that receive more satellite signals. The proposed method generates the artificial potential fields from the satellite visibility map and obstacle information around the vehicle, and it generates the path following the potential fields. Thereby, the vehicle can select the path that has more satellite signals, improving the availability of GPS fixed solutions. Hence, the vehicle can reduce the accumulated error by dead reckoning, and it can improve the safety of self-control. In this study, we evaluate the satellite visibility maps and the path planning method. The results show that the proposed method does improve the availability of GPS fixed solutions.

Cite this article as:
Mitsunori Kitamura, Yoichi Yasuoka, Taro Suzuki,
Yoshiharu Amano, and Takumi Hashizume, “Path Planning for Autonomous Vehicles Using QZSS and Satellite Visibility Map,” J. Robot. Mechatron., Vol.25, No.2, pp. 400-407, 2013.
Data files:
References
  1. [1] D. D’Incà and P. Zatelli, “New modules for satellite surveying planning in GRASS,” 3th and 4th Italian GRASS users meeting proceedings, Geomatics Workbooks, Vol.3, Feb. 2004.
  2. [2] J. Meguro, R. Hirokawa, J. Takiguchi, and T. Hashizume, “Autonomous Mobile Surveillance System based on RTK-GPS in Urban Canyons,” J. of Robotics and Mechatronics, Vol.2, No.17, pp. 218-225, 2005.
  3. [3] “Quasi-Zenith Satellite System Navigation Service Interface Specification for QZSS IS-QZSS Ver.1.4,” Japan Aerospace Exploration Agency, Feb. 2012.
  4. [4] K. Ishikawa, J. Takiguchi, Y. Amano, and T. Hashizume, “A Mobile Mapping System for road data capture based on 3D road model,” IEEE Int. Conf. on Control Applications, Munich, Germany, 2006.
  5. [5] D. Hanandhar and R. Shibasaki, “Vehicle-Borne Laser Mapping System (VLMS) FOR 3-D GIS,” Geoscience and Remote Sensing Symposium, 2001 (IGARSS ’01), pp. 2073-2075, 2001.
  6. [6] O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” The Int. J. of Robotics Research, Vol.5, No.1, pp. 90-98, Mar. 1986.
  7. [7] P. Khosla and R. Volpe, “Superquadratic Artificial Potentials for Obstacle Avoidance and Approach,” Proc. of the IEEE Conf. on Robotics and Automation (ICRA ’88), pp. 1778-1784, Apr. 1988.
  8. [8] J. Barraquand and J. Latombe, “Robot Motion Planning: A Distributed Representation Approach,” The Int. J. of Robotics Research, Vol.10, No.6, pp. 628-649, Dec. 1991.
  9. [9] J. A. Sethian, “A fast marching level set method for monotonically advancing fronts,” Proc. Natl. Acad. Sci. USA, Vol.93, pp. 1591-1595, Feb. 1996.
  10. [10] C. H. Chiang, P. J. Chiang, J. C.-C. Fei, and J. S. Liu, “A comparative study of implementing Fast Marching Method and A*SEARCH for mobile robot path planning in grid environment: Effect of map resolution,” Advanced Robotics and Its Social Impacts 2007, pp. 1-6, Dec. 2007.
  11. [11] M. Kitamura, T. Suzuki, Y. Amano, and T. Hashizume, “Improvement of GPS and GlONASS Positioning Accuracy by Multipath Mitigation Using Omni Directional Infrared Camera,” J. of Robotics and Mechatronics, Vol.23, No.6, pp. 1125-1131, Dec. 2011.

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

Last updated on May. 14, 2021