Development of a radiation resistant laser scanner and 3D modeling method using AI and image processing (Contract research); FY2024 Nuclear Energy Science & Technology and Human Resource Development Project

Collaborative Laboratories for Advanced Decommissioning Science; The University of Osaka*

JAEA-Review 2026-009, 81 Pages, 2026/07

JAEA-Review-2026-009.pdf:5.42MB

The Collaborative Laboratories for Advanced Decommissioning Science (CLADS), Japan Atomic Energy Agency (JAEA), has been conducting the Nuclear Energy Science & Technology and Human Resource Development Project (hereafter referred to "the Project") from FY2019. The Project aims to contribute to solving problems in the nuclear energy field represented by the decommissioning of the Fukushima Daiichi Nuclear Power Station, Tokyo Electric Power Company Holdings, Inc. (TEPCO). For this purpose, intelligence was collected from all over the world, and basic research and human resource development were promoted by closely integrating/collaborating knowledge and experiences in various fields beyond the barrier of conventional organizations and research fields. The sponsor of the Project was moved from the Ministry of Education, Culture, Sports, Science and Technology to JAEA since the newly adopted proposals in FY2018. On this occasion, JAEA constructed a new research system where JAEA-academia collaboration is reinforced and medium-to-long term research/development and human resource development contributing to the decommissioning are stably and consecutively implemented. Among the adopted proposals in FY2024, this report summarizes the research results of the "Development of a radiation resistant laser scanner and 3D modeling method using AI and image processing" conducted in FY2024. This research focuses on developing a radiation-resistant 3D laser scanner and technologies to enhance the quality of point cloud data. A new scanner system was designed with a laser scanning head composed only of radiation-tolerant electrical and mechanical components, excluding semiconductors, and a control unit placed remotely in a low-radiation zone. The system aims to enable stable scanning in high-radiation environments. Its performance will be evaluated in comparison with commercial scanners. To address the sparsity of acquired point clouds, we are developing two complementary systems: one uses machine learning to complete and enhance point clouds through processes such as denoising, normalization, and interpolation; the other uses photogrammetry to reconstruct 3D data from image sets and integrate it with scanner-derived data. In FY2024, (1) Optical and electronic circuits were designed and assembled, and waveform collection and analysis software was developed to prepare for scanner detection efficiency evaluation. (2) A point cloud completion system incorporating AI was implemented, and methods for point cloud densification and completion were investigated. (3) A processing environment and workflow were established to integrate point clouds with photogrammetry, and 3D surface models were constructed. (4) Efficient scanning strategies under high-radiation conditions were analyzed, and a methodology for accuracy evaluation was studied. (5) The project was advanced through close coordination among research components and related institutions.

Radiation imaging using a compact Compton camera mounted on a crawler robot inside reactor buildings of Fukushima Daiichi Nuclear Power Station

Sato, Yuki; Terasaka, Yuta; Utsugi, Wataru*; Kikuchi, Hiroyuki*; Kiyooka, Hideo*; Torii, Tatsuo

Journal of Nuclear Science and Technology, 56(9-10), p.801 - 808, 2019/09

https://doi.org/10.1080/00223131.2019.1581111

Visualization of radioactive substances on a 3D building model of the Fukushima Daiichi Nuclear Power Station

Sato, Yuki; Terasaka, Yuta; Utsugi, Wataru*; Kikuchi, Hiroyuki*; Takahira, Shiro*; Torii, Tatsuo

no journal, , 

Visualization of radioactive substances by integrating radiation measurement, remote technology, and 3-D optical measurement

Sato, Yuki; Terasaka, Yuta; Kaburagi, Masaaki; Tanifuji, Yuta; Torii, Tatsuo

no journal, ,