single-rb.php

JRM Vol.28 No.4 pp. 461-469
doi: 10.20965/jrm.2016.p0461
(2016)

Paper:

Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015

Tomoyoshi Eda, Tadahiro Hasegawa, Shingo Nakamura, and Shin’ichi Yuta

Shibaura Institute of Technology
3-7-5 Toyosu, Koto-ku, Tokyo 135-8548, Japan

Received:
March 10, 2016
Accepted:
May 30, 2016
Published:
August 20, 2016
Keywords:
autonomous mobile robot, Tsukuba Challenge 2015, map matching, wheel odometry, downhill simplex method
Abstract
This paper describes a self-localization method for autonomous mobile robots entered in the Tsukuba Challenge 2015. One of the important issues in autonomous mobile robots is accurately estimating self-localization. An occupancy grid map, created manually before self-localization has typically been utilized to estimate the self-localization of autonomous mobile robots. However, it is difficult to create an accurate map of complex courses. We created an occupancy grid map combining local grid maps built using a leaser range finder (LRF) and wheel odometry. In addition, the self-localization of a mobile robot was calculated by integrating self-localization estimated by a map and matching it to wheel odometry information. The experimental results in the final run of the Tsukuba Challenge 2015 showed that the mobile robot traveled autonomously until the 600 m point of the course, where the occupancy grid map ended.
Autonomous mobile robots entered in the Tsukuba Challenge 2015

Autonomous mobile robots entered in the Tsukuba Challenge 2015

Cite this article as:
T. Eda, T. Hasegawa, S. Nakamura, and S. Yuta, “Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015,” J. Robot. Mechatron., Vol.28 No.4, pp. 461-469, 2016.
Data files:
References
  1. [1] J. Eguchi and K. Ozaki, “Development of the Autonomous Mobile Robot for Target-Searching in Urban Areas in the Tsukuba Challenge 2013,” J. of Robot Mechatronics, Vol.26, No.2, pp. 166-175, 2014.
  2. [2] T. Tomizawa, S. Muramatsu, M. Sato, M. Hirai, S. Kudoh, and T. Suehiro, “Development of an Intelligent Senior-Car in a Pedestrian Walkway,” Advanced Robotics, Vol.26, No.14, 2012.
  3. [3] M. Yokozuka, Y. Suzuki, T. Takei, N. Hashimoto, and O. Matsumoto, “Auxiliary Particle Filter Localization for Intelligent Wheelchair Systems in Urban Environments,” J. of Robot Mechatronics, Vol.22, No.6, pp. 758-765, 2012.
  4. [4] N. Akai, K. Inoue, and K. Ozaki, “Autonomous navigation based on magnetic and geometric landmarks on environmental structure in real world,” J. Robot Mechatronics, Vol.26, No.2, pp. 158-165, 2014.
  5. [5] H. Date and Y. Takita, “Real World Experiments of Autonomous Mobile Robot Smart Dump –Influence and Countermeasure of Human Crowd Behavior in a Pedestrian Environment –,” J. of the Robotics Society of Japan, Vol.30, No.3, pp. 305-313, 2012 (in Japanese).
  6. [6] M. Tomono, T. Yoshida, K. Irie, and E. Koyanagi, “Analysis and Design of Outdoor Navigation Systems at the Tsukuba Challenge,” J. of the Robotics Society of Japan, Vol.30, No.3, pp. 262-270, 2012 (in Japanese).
  7. [7] E. Takeuchi, T. Tsubouchi, and S. Yuta, “Integration and Synchronization of External Sensor Data for a Mobile Robot,” SICE Annual Conf. 2003, pp. 1019-1020, 2003.
  8. [8] S. Iida and S. Yuta, “Vehicle Command System and Trajectory Control for Autonomous Mobile Robots,” Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS’91), 1991.
  9. [9] K. Okawa, “Position Estimation for Outdoor Mobile Robot by Downhill Simplex Method,” Proc. of 15th SICE Symposium on System Integration (SI2014), 1F1-1, 2014 (in Japanese).

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

Last updated on Apr. 05, 2024