JRM Vol.30 No.4 pp. 540-551
doi: 10.20965/jrm.2018.p0540


Person Searching Through an Omnidirectional Camera Using CNN in the Tsukuba Challenge

Shingo Nakamura, Tadahiro Hasegawa, Tsubasa Hiraoka, Yoshinori Ochiai, and Shin’ichi Yuta

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

February 26, 2018
June 19, 2018
August 20, 2018
omnidirectional camera, person searching, convolutional neural networks, Tsukuba Challenge

The Tsukuba Challenge is a competition, in which autonomous mobile robots run on a route set on a public road under a real environment. Their task includes not only simple running but also finding multiple specific persons at the same time. This study proposes a method that would realize person searching. While many person-searching algorithms use a laser sensor and a camera in combination, our method only uses an omnidirectional camera. The search target is detected using a convolutional neural network (CNN) that performs a classification of the search target. Training a CNN requires a great amount of data for which pseudo images created by composition are used. Our method is implemented in an autonomous mobile robot, and its performance has been verified in the Tsukuba Challenge 2017.

An autonomous robot finding a target person using the proposed method

An autonomous robot finding a target person using the proposed method

Cite this article as:
S. Nakamura, T. Hasegawa, T. Hiraoka, Y. Ochiai, and S. Yuta, “Person Searching Through an Omnidirectional Camera Using CNN in the Tsukuba Challenge,” J. Robot. Mechatron., Vol.30 No.4, pp. 540-551, 2018.
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