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JRM Vol.31 No.2 p. 179
doi: 10.20965/jrm.2019.p0179
(2019)

Editorial:

Special Issue on Probabilistic Robotics and SLAM

Keigo Watanabe, Shoichi Maeyama, Tetsuo Tomizawa, Ryuichi Ueda, and Masahiro Tomono

Specially Appointed Professor, Graduate School of Natural Science and Technology, Okayama University
3-1-1 Tsushima-naka, Kita-ku, Okayama-shi, Okayama 700-8530, Japan
Professor, Faculty of Engineering and Design, Kagawa University
2217-20 Hayashicho, Takamatsu, Kagawa 761-0396, Japan
Lecturer, Department of Computer Science, National Defense Academy of Japan
1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan
Associate Professor, Department of Advanced Robotics, Chiba Institute of Technology
2-17-1 Tsudanuma, Narashino, 275-0016 Chiba, Japan
Deputy Director, Future Robotics Technology Center, Chiba Institute of Technology
2-17-1 Tsudanuma, Narashino, 275-0016 Chiba, Japan

Published:
April 20, 2019

Intelligent mobile robots need self-localization, map generation, and the ability to explore unknown environments autonomously. Probabilistic processing can be applied to overcome the problems of movement uncertainties and measurement errors. Probabilistic robotics and simultaneous localization and mapping (SLAM) technologies are therefore strongly related, and they have been the focus of many studies. As more and more practical applications are found for intelligent mobile robots, such as for autonomous driving and cleaning, the applicability of these techniques has been increasing.

In this special issue, we provide a wide variety of very interesting papers ranging from studies and developments in applied SLAM technologies to fundamental theories for SLAM. There are five academic papers, one each on the following topics: first visit navigation, controls for following rescue clues, indoor localization using magnetic field maps, a new solution for self-localization using downhill simplex method, and object detection for long-term map management through image-based learning. In addition, in the next number, there will be a review paper by Tsukuba University’s Prof. Tsubouchi, who is famous for the Tsukuba Challenge and research related to mobile robotics.

We editors hope this special issue will help readers to develop mobile robots and use SLAM technologies and probabilistic approaches to produce successful applications.

Cite this article as:
K. Watanabe, S. Maeyama, T. Tomizawa, R. Ueda, and M. Tomono, “Special Issue on Probabilistic Robotics and SLAM,” J. Robot. Mechatron., Vol.31, No.2, p. 179, 2019.
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Last updated on May. 20, 2019