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

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

Autonomous mobile robots entered in the Tsukuba Challenge 2015

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.

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, IE9,10,11, Opera.

Last updated on Nov. 20, 2018