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IJAT Vol.19 No.3 pp. 178-191
doi: 10.20965/ijat.2025.p0178
(2025)

Research Paper:

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Change Detection in Image Pairs for Plant Inspection Using Mobile Robot

Susumu Shimizu*1 ORCID Icon, Takuya Igaue*1,† ORCID Icon, Jun Younes Louhi Kasahara*1 ORCID Icon, Naoya Yamato*2, Seiji Kasahara*2, Hiroyuki Ito*2, Taizo Daito*2, Sunao Tamura*2, Akinobu Sasamura*2, Toshiya Kato*2, Fumihiko Nonaka*2, Shinji Kanda*3 ORCID Icon, Keiji Nagatani*1 ORCID Icon, Hajime Asama*1 ORCID Icon, Qi An*4 ORCID Icon, and Atsushi Yamashita*4 ORCID Icon

*1Department of Precision Engineering, Graduate School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

†Corresponding author

*2Engineering & Capital Planning Department, ENEOS Corporation
Tokyo, Japan

*3Research into Artifacts, Center for Engineering, The University of Tokyo
Tokyo, Japan

*4Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo
Kashiwa, Japan

Received:
August 20, 2024
Accepted:
November 29, 2024
Published:
May 5, 2025
Creative Commons License
Keywords:
robot system, image change detection, autonomous plant inspection
Abstract

In this study, we propose a system to detect changes in three-dimensional (3D) space for autonomous plant visual inspection by a mobile robot. The videos captured by a mobile robot during past inspections are compared with the videos obtained during the current inspection using both pose information and the acquired images. To ensure robustness against changes in shooting conditions, change detection is executed employing deep learning techniques. Subsequently, the detected information is projected onto a 3D space to localize the changes. To verify the effectiveness of the proposed method, experiments were conducted both in a real plant environment and a simulated indoor plant environment. The results of the outdoor experiments showed that the proposed system achieved image pair determination, change detection, and integration into a 3D space. The results of the indoor experiments and evaluations confirmed that the proposed method for image pair determination was suitable based on considerations of detection accuracy and computation time.

Cite this article as:
S. Shimizu, T. Igaue, J. Kasahara, N. Yamato, S. Kasahara, H. Ito, T. Daito, S. Tamura, A. Sasamura, T. Kato, F. Nonaka, S. Kanda, K. Nagatani, H. Asama, Q. An, and A. Yamashita, “Change Detection in Image Pairs for Plant Inspection Using Mobile Robot,” Int. J. Automation Technol., Vol.19 No.3, pp. 178-191, 2025.
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Last updated on May. 30, 2025