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Journal Articles

Rail DRAGON: Long-reach Bendable Modularized Rail Structure for Constant Observation inside PCV

Yokomura, Ryota*; Goto, Masataka*; Yoshida, Takehito*; Warisawa, Shinichi*; Hanari, Toshihide; Kawabata, Kuniaki; Fukui, Rui*

IEEE Robotics and Automation Letters (Internet), 9(4), p.3275 - 3282, 2024/04

To reduce errors in the remote control of robots during decommissioning, we developed a Rail DRAGON, which enables continuous observation of the work environment. The Rail DRAGON is constructed by assembling and pushing a long rail structure inside the primary containment vessel (PCV), and then repeatedly deploying several monitoring robots on the rails to enable constant observation in a high-radiation environment. In particular, we have developed the following components of Rail DRAGON: bendable rail modules, straight rail modules, a basement unit, and monitoring robots. Concretely, this research proposes and demonstrates a method to realize an ultralong articulated structure with high portability and workability. In addition, it proposes and verifies the feasibility of a method for deploying observation equipment that can be easily deployed and replaced, while considering disposal.

Journal Articles

A Study on the effects of photogrammetry by the camera angle of view using computer simulation

Nakamura, Keita; Hanari, Toshihide; Matsumoto, Taku; Kawabata, Kuniaki; Yashiro, Hiroshi*

Journal of Robotics and Mechatronics, 36(1), p.115 - 124, 2024/02

Journal Articles

Integration of multiple partial point clouds based on estimated parameters in photogrammetry with QR codes

Baba, Keita*; Watanobe, Yutaka*; Nakamura, Keita*; Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of 29th International Symposium on Artificial Life and Robotics (AROB 2024) (Internet), p.751 - 756, 2024/01

Journal Articles

Automatic system for sequential reconstruction from image sequences acquired from a camera by SfM-MVS

Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki; Yashiro, Hiroshi*; Nakamura, Keita*

Proceedings of 2023 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2023) (Internet), 7 Pages, 2023/12

JAEA Reports

Annual report for FY2021 on the activities of Naraha Center for Remote Control Technology Development (April 1, 2021 - March 31, 2022)

Akiyama, Yoichi; Shibanuma, So; Yanagisawa, Kenichi*; Yamada, Taichi; Suzuki, Kenta; Yoshida, Moeka; Ono, Takahiro; Kawabata, Kuniaki; Watanabe, Kaho; Morimoto, Kyoichi; et al.

JAEA-Review 2023-015, 60 Pages, 2023/09

JAEA-Review-2023-015.pdf:4.78MB

Naraha Center for Remote Control Technology Development (NARREC) was established in Japan Atomic Energy Agency to promote a decommissioning work of Fukushima Daiichi Nuclear Power Station (Fukushima Daiichi NPS). NARREC consists of a Full-scale Mock-up Test Building and Research Management Building. Various test facilities are installed in these buildings for the decommissioning work of Fukushima Daiichi NPS. These test facilities are intended to be used for various users, such as companies engaged in the decommissioning work, research and development institutions, educational institutions and so on. The number of NARREC facility uses was 84 in FY2021. We participated booth exhibitions and presentations on the decommissioning related events. Moreover, we also contributed to the development of human resources by supporting the 6th Creative Robot Contest for Decommissioning. As a new project, "Narahakko Children's Classroom" was implemented for elementary school students in Naraha Town. This report summarizes the activities of NARREC in FY2021, such as the utilization of facilities and equipment of NARREC, the development of remote-control technologies for supporting the decommissioning work, arrangement of the remote-control machines for emergency response, and training for operators by using the machines.

Journal Articles

Integration of 3D environment models generated from the sections of the image sequence based on the consistency of the estimated camera trajectories

Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki; Yashiro, Hiroshi*; Nakamura, Keita*

Proceedings of 22nd World Congress of the International Federation of Automatic Control (IFAC 2023) (Internet) , p.12107 - 12112, 2023/07

Journal Articles

Image selection method from image sequence to improve computational efficiency of 3D reconstruction; Application of robust threshold based on multimodal test to images

Hanari, Toshihide; Kawabata, Kuniaki; Nakamura, Keita*

Proceedings of 22nd World Congress of the International Federation of Automatic Control (IFAC 2023) (Internet) , p.11597 - 11602, 2023/07

This paper describes the image selection method by multimodal detection for improving the computational efficiency of three-dimensional (3D) reconstruction based on images in a time-series. To decrease the calculation time of the 3D reconstruction, an adequate selection from the images is required. For this reason, we introduced multimodal detection by a statistical test on the image selection process, and then applied it to soundness evaluation of the displacements based on the optical flow between images acquired by a camera. The results suggest that suitable images can be extracted from the images in a time-series for decreasing the calculation time of the 3D reconstruction. Therefore, the suitable images selected by the proposed method contributed to efficiently performing the 3D reconstruction.

Journal Articles

Development of performance evaluation methods for small unmanned aircraft systems flying in constrained environment

Kawabata, Kuniaki; Sato, Noritaka*

Keisoku To Seigyo, 62(5), p.276 - 279, 2023/05

no abstracts in English

Journal Articles

3D reconstruction considering calculation time reduction for linear trajectory shooting and accuracy verification with simulator

Nakamura, Keita; Hanari, Toshihide; Kawabata, Kuniaki; Baba, Keita*

Artificial Life and Robotics, 28(2), p.352 - 360, 2023/02

Journal Articles

Discrimination of structures in a plant facility based on projected image created from colored 3D point cloud data

Imabuchi, Takashi; Kawabata, Kuniaki

Proceedings of 2023 IEEE/SICE International Symposium on System Integration (SII 2023) (Internet), p.396 - 400, 2023/01

Journal Articles

Automatic process for 3D environment modeling from acquired image sequences

Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki; Yashiro, Hiroshi*; Nakamura, Keita*

Proceedings of 28th International Symposium on Artificial Life and Robotics (AROB 28th 2023) (Internet), p.768 - 773, 2023/01

Journal Articles

Development of PHITSPlugin for Radiation Behavior Calculation

Suzuki, Kenta; Yashiro, Hiroshi*; Kawabata, Kuniaki

Proceedings of International Topical Workshop on Fukushima Decommissioning Research (FDR2022) (Internet), 4 Pages, 2022/10

JAEA Reports

HAIROWorldPlugin operation manual (Revised edition)

Suzuki, Kenta; Yashiro, Hiroshi; Kawabata, Kuniaki

JAEA-Testing 2021-004, 125 Pages, 2022/03

JAEA-Testing-2021-004.pdf:6.1MB

This report is updated HAIROWorldPlugin Operation Manual (JAEA-Testing 2020-009). Our motivation is to develop a robot simulator based on Choreonoid for technological development to contribute the decommissioning work at the Fukushima Daiichi Nuclear Power Station of Tokyo Electric Power Company Holdings, Inc. Choreonoid is an open source simulator which calculates the behavior of robots. We are developing HAIROWorldPlugin which is an extended function of Choreonoid for providing a virtual decommissioning experience. In the latest HAIROWorldPlugin, the several functions were additionally implemented. In particular, we implemented new functionalities: logging a collision status between a robot and an object, showing and logging a status of the joystick input signals, generating an environmental object model (pipe, grating, and slope), bookmarking an often used simulation settings, and recording histories of a simulation settings. In addition, this report describes the installation of the plugin to Choreonoid on Ubuntu20.04-LTS and parameter settings of the plugin by presenting snapshots of operation windows.

JAEA Reports

Test methods for robots for nuclear emergency response and decommissioning; Test for maneuvering robot arm over an obstacle (JAEA-TM-0006)

Yamada, Taichi; Kawabata, Kuniaki; Abe, Hiroyuki*

JAEA-Technology 2021-033, 18 Pages, 2022/03

JAEA-Technology-2021-033.pdf:1.58MB

This report describes the test procedures for evaluating performances involved in robot arm maneuvering of remotely operated robot utilized for nuclear emergency responses and decommissioning. After the accident at Fukushima Daiichi Nuclear Power Station of the Tokyo Electric Power Company Holdings Inc. (FDNPS) occurred, remotely operated robots have been deployed and utilized in the response tasks. Such post-accident work experience and lessons learned are very valuable for developing the robots in the future. Therefore, we were motivated to develop the test methods for performance evaluation of the robot by referring with such experiences and lessons. In the response and the decommissioning tasks, robots with a robot arm were deployed for door opening, removal objects, decontamination and cleanup and so on. Some of these tasks were conducted in an environment with obstacles by robot arms maneuvering. This report describes test procedures for quantitatively evaluating the performances which are for maneuvering involving in robot arm to approach target objects in an environment with obstacles. A typical course layout and the demonstration of test are also illustrated for the references.

Journal Articles

Discrimination of the structures in nuclear facility by deep learning based on 3D point cloud data

Imabuchi, Takashi; Tanifuji, Yuta; Kawabata, Kuniaki

Proceedings of 2022 IEEE/SICE International Symposium on System Integration (SII 2022) (Internet), p.1036 - 1040, 2022/01

This paper describes a method for discrimination of the structures in nuclear power station by deep learning based on 3D point cloud data. In order to promote safe and steady decommissioning work, it is important to estimate and assume the condition in nuclear power station based on the measured sensor data. Especially, the data of the dose rate in the workspace is useful to plan the decommissioning task and, the shape and the material property of the structures in the workspace are required for the dose rate simulation. Shape data can be obtained by such as 3D Scan, however, it is difficult to acquire the material property data of the objects. Therefore, we consider that it is possible that the major material property can be estimated from the category of the structures in nuclear power station. In this paper, we proposed a structure discrimination method by 3D semantic segmentation with 3D point cloud data that consists of labeled points by referring category labels of CAD data of existing nuclear facility. We reported discrimination performance of the proposed method by hold-out validation.

Journal Articles

Image selection method from image sequence to improve computational efficiency of 3D reconstruction; Analysis of inter-image displacement based on optical flow for evaluating 3D reconstruction performance

Hanari, Toshihide; Kawabata, Kuniaki; Nakamura, Keita

Proceedings of 2022 IEEE/SICE International Symposium on System Integration (SII 2022) (Internet), p.1041 - 1045, 2022/01

 Times Cited Count:2 Percentile:88.99

This paper describes the image selection method for an efficient three-dimensional (3D) reconstruction computation from an image sequence. Adequate images must be selected from the image sequence to improve the computational efficiency of the 3D reconstruction. Thus, we investigated a threshold based on the displacement among images obtained from a camera mounted on a remotely operated robot. The results confirmed that the proposed method can select adequate images for efficient 3D reconstruction by the threshold based on the optical flow from the image sequence. Therefore, the computational cost could be reduced by eliminating the duplicate and high-similarity images to perform the efficient 3D reconstruction.

Journal Articles

3D reconstruction considering calculation time reduction for linear trajectory shooting

Nakamura, Keita; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of 27th International Symposium on Artificial Life and Robotics (AROB 27th 2022) (Internet), p.771 - 775, 2022/01

In three-dimensional (3D) reconstruction from images, even if the number of images is small and each image captures the features of the target object for 3D reconstruction, highly accurate 3D reconstruction can be achieved in a short time. Therefore, to select effective images for 3D reconstruction, we consider that test data for image selection can be generated by constructing a virtual space using simulation and changing the shooting conditions. In this study, we focus on the case that a camera moves on a straight rail and obtains images, and investigate and verify the effective image selection conditions considering calculation time reduction for 3D reconstruction in this case by simulation.

Journal Articles

Development of PHITS plugin for calculating the integral radiation dose on robots

Suzuki, Kenta; Kawabata, Kuniaki

New Trends in Intelligent Software Methodologies, Tools and Techniques; Frontiers in Artificial Intelligence and Applications, Vol.355, p.248 - 257, 2022/00

JAEA Reports

Test methods for robots for nuclear emergency response and decommissioning; Tests for moving performances of robots (JAEA-TM-0004 and JAEA-TM-0005)

Kawabata, Kuniaki; Yamada, Taichi; Abe, Hiroyuki*

JAEA-Technology 2021-021, 30 Pages, 2021/11

JAEA-Technology-2021-021.pdf:2.55MB

This report describes the test procedures for performance evaluation of remotely operated robot utilized for nuclear emergency responses and decommissioning that provide to compare among the robot's performances quantitatively and relatively. After the accident at Fukushima Daiichi Nuclear Power Station of the Tokyo Electric Power Company Holdings Inc. (FDNPS) occurred, remotely operated robots have been deployed and utilized in the response tasks. Such post-accident work experiences and lessons learned are very valuable for developing the robots in the future. Therefore, we were motivated to develop the test methods for performance evaluation of the robot by referring with such experiences and lessons. In recent decommissioning tasks, reconnaissance on the distribution and status of nuclear fuel debris inside the Primary Containment Vessel (PCV) have been carried out. The insertion and deployment of robots into PCV were carried out through a penetration pipe with small diameter to prevent the scattering of radioactive materials. According to the authors' survey on such works have carried out in Units 1 and 2 of FDNPS, in order to carry out the reconnaissance work by the robot deployed into the PCV, it was clarified that the robots are required to run freely on the floor located below the exit of the penetration pipe and run freely on the inclined surface located below the exit of the pipe. This document describes two test procedures for performance evaluation of the robot connected with the cable such as running on the floor after being deployed through a penetration pipe and running on the inclined surface after being deployed through a penetration pipe. Typical course layout and the demonstration of test running are also illustrated for the references.

Journal Articles

Tracking method of medaka considering proximity state

Sakakibara, Takanori*; Takahashi, Satoru*; Kawabata, Kuniaki; Oda, Shoji*

2021 IEEE/SICE International Symposium on System Integration (SII 2021), Vol.2, p.517 - 523, 2021/07

 Times Cited Count:0 Percentile:0

In biology, it is expected to understand the mechanism of herd development by analyzing crowd behavior. Currently, medaka (Oryzias latipes) is often used when conducting such research because of its ease of breeding and experimentation. However, when conducting such studies, it is very difficult to manually obtain herd data. In this article, in order to analyze the behavior of medaka, we will introduce a method to automatically extract the swimming trajectory of medaka from time-series images and acquire the data necessary for behavior analysis. In particular, the improvement of extraction accuracy is achieved by processing the overlap state and adjoin state of medaka in the image.

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