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今渕 貴志; 羽成 敏秀; 川端 邦明
Proceedings of 2025 IEEE/SICE International Symposium on System Integration (SII2025), p.1416 - 1421, 2025/01
This paper describes a 3D reconstruction based on grouping similar structures for the aim of generating 3D information for understanding the workspace from the images acquired inside the Primary Containment Vessel (PCV) of the Fukushima Daiichi Nuclear Power Station. In the decommissioning works, preliminary surveys are carried out in the PCV, and the workers need to understand the workspace from a large amount of camera images, which requires a great deal of effort. We are currently working on 3D reconstruction from camera images of the PCV, however, one of the challenges is to improve the visibility of reconstructed model containing noise and artifact. In this study, we propose a method of grouping similar structures on the image and utilizing predicted group labels for 3D reconstruction process to highlight structures shapes and to refine 3D modeling. Our key idea is to perform unsupervised segmentation for grouping similar structures that are suitable for images acquired in the PCV because they are difficult to assign correct semantics for unclear structures and the few learning resources. We show on the reasonable performance of our method by validating it by video images of a typical plant environment and survey videos of the PCV taken under adverse conditions such as radiation noise.
羽成 敏秀; 中村 啓太*; 今渕 貴志; 川端 邦明
Journal of Robotics and Mechatronics, 36(6), p.1537 - 1549, 2024/12
本稿では、時系列画像から3次元モデルを効率的に生成するための画像選択法を導入した立体復元処理について述べる。効率的な立体復元に適した画像を得るために、時系列画像中の冗長画像を除去する画像選択法の適用を試みた。提案手法では、オプティカルフローと固定しきい値に基づいて、時系列画像から適切な画像を選択する。その結果、提案手法により、カメラで取得した時系列画像に基づく立体復元処理の計算量を削減することができた。その結果、立体復元精度を一定に保ったまま、立体復元処理の計算量を削減できることを確認した。
中島 慎介*; Moro, A.*; 小松 廉*; Faragasso, A.*; 松日楽 信人*; Woo, H.*; 川端 邦明; 山下 淳*; 淺間 一*
Proceedings of International Topical Workshop on Fukushima-Daiichi Decommissioning Research 2024 (FDR2024) (Internet), 4 Pages, 2024/10
Fuel debris retrieval at the bottom of the primary containment vessel (PCV) is one of the significant tasks for the decommissioning of the nuclear power plant and in particular for 1F. It is challenging for conventional manipulators to perform the retrieval process due to the presence of radiation, water leakage, and poor lighting conditions. We tackle those problems with the design and fabrication of a novel mechanical manipulator and its control and navigation algorithm. Continuous Variable Transmission (CVT)-based actuation improves the robot's shock resistance. AI-based navigation algorithm enables semiautonomous navigation and grasping in the cluttered environment inside the PCV.
中村 啓太*; 馬場 啓多*; 渡部 有隆*; 羽成 敏秀; 松本 拓*; 今渕 貴志; 川端 邦明
Artificial Life and Robotics, 29(4), p.546 - 556, 2024/09
This paper describes a method for integrating multiple dense point clouds using a shared landmark to generate a single real-scale integrated result for photogrammetry. It is difficult to integrate high-density point clouds reconstructed by photogrammetry because the scale differs with each photogrammetry. To solve this problem, this study places a QR code of known sizes, which is a shared landmark, in the reconstruction target environment and divides the reconstruction target environment based on the position of the QR code that is placed. Then, photogrammetry is performed for each divided environment to obtain each high-density point cloud. Finally, we propose a method of scaling each high-density point cloud based on the size of the QR code and aligning each high-density point cloud as a single high-point cloud by partial-to-partial registration. To verify the effectiveness of the method, this paper compares the results obtained by applying all images to photogrammetry with those obtained by the proposed method in terms of accuracy and computation time. In this verification, ideal images generated by simulation and images obtained in real environments are applied to photogrammetry. We clarify the relationship between the number of divided environments, the accuracy of the reconstruction result, and the computation time required for the reconstruction.
川端 邦明; 今渕 貴志; 白崎 令人*; 鈴木 壮一郎; 伊藤 倫太郎; 青木 勇斗; 大森 崇純
ROBOMECH Journal (Internet), 11, p.11_1 - 11_11, 2024/09
This paper describes a measuring unit to realize the synchronous collection of air dose rate and measurement position for efficient dosimetry survey and data logging in a working space. The developed prototype comprises a three-dimensional light detection and ranging-based mapping part and a dosimetry part, which are integrated into a single measurement unit through an embedded computer that installs a ROS (Robot Operating System) framework. The unit can function as a standalone system with embedded batteries. Since it is portable, on-line data gathering in the workspace can be realized, thereby maintaining consistency between the air dose rate and the measurement position. In this paper, we describe the prototype system configuration and the experimental results obtained in the mockup test space and nuclear facility to discuss its performance.
中村 啓太*; 羽成 敏秀; 今渕 貴志; 川端 邦明
Proceedings of 2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2024), p.7 - 8, 2024/07
写真測量法は、対象物を撮影した複数の画像から3次元的に復元する技術である。実際の撮影では、対象物を撮影するカメラの画角に振動が発生し、写真測量に適した画像を撮影できず、対象物を復元できない場合がある。そこで、この振動をシミュレーション上で乱数を用いて実装し、振動の大きさが写真測量法で得られる復元結果に与える影響を検証した。検証の結果、振動の大きさと3次元復元の成功率との関係が示された。
松本 拓; 羽成 敏秀; 川端 邦明; 中村 啓太*; 八代 大*
Artificial Life and Robotics, 29(2), p.358 - 371, 2024/05
This paper describes a three-dimensional (3D) modeling method for sequentially and spatially understanding situations in unknown environments from an image sequence acquired from a camera. The proposed method chronologically divides the image sequence into sub-image sequences by the number of images, generates local 3D models from the sub-image sequences by the Structure from Motion and Multi-View Stereo (SfM-MVS), and integrates the models. Images in each sub-image sequence partially overlap with previous and subsequent sub-image sequences. The local 3D models are integrated into a 3D model using transformation parameters computed from a camera trajectory estimated by the SfM-MVS. In our experiment, we quantitatively compared the quality of integrated models with a 3D model generated from all images in a batch and the computational time to obtain these models using three real data sets acquired from a camera. Consequently, the proposed method can generate a quality integrated model that is compared with a 3D model using all images in a batch by the SfM-MVS and reduce the computational time.
横村 亮太*; 後藤 雅貴*; 吉田 健人*; 割澤 伸一*; 羽成 敏秀; 川端 邦明; 福井 類*
IEEE Robotics and Automation Letters (Internet), 9(4), p.3275 - 3282, 2024/04
被引用回数：0 パーセンタイル：0.00(Robotics)廃炉作業におけるロボットの遠隔操作のエラーを低減するため、作業環境を常時観察できるRail DRAGONを開発した。Rail DRAGONは、原子炉格納容器(PCV)内に長尺の軌道構造体(レールモジュール)を組み立てて押し込み、そのレール上に複数台のモニタリングロボットを繰り返し配置することで構築され、高放射線環境下での常時監視を可能にしたものである。特に、Rail DRAGONの構成要素である屈曲可能なレールモジュール、直線状のレールモジュール、基部ユニット、モニタリングロボットを開発した。具体的には、可搬性・作業性に優れた超長尺多関節構造物の実現手法を提案・実証している。また、処分を考慮しつつ、容易に展開・交換が可能な観測機器の展開手法を提案し、その実現可能性を検証する。
今渕 貴志; 川端 邦明
Journal of Robotics and Mechatronics, 36(1), p.63 - 70, 2024/02
In the decommissioning of Fukushima Daiichi Nuclear Power Station, radiation dose calculations using a 3D model of the workspace are performed to determine appropriate measures to reduce exposure. However, constructing a 3D model from 3D point cloud is costly. In order to separate the geometrical shape regions on 3D point cloud, we have been developing the structure discrimination method by 3D and 2D deep learning for contributing to 3D modeling automation technology. In this paper, we describe a method for transferring and fusing labels to handle 2D prediction label in 3D space. We propose an exhaustive label fusion method for plant facilities with intricate structures. In evaluation, we applied the method to a mock-up plant dataset and confirmed that it works effectively.
中村 啓太; 羽成 敏秀; 松本 拓; 川端 邦明; 八代 大*
Journal of Robotics and Mechatronics, 36(1), p.115 - 124, 2024/02
During the decommissioning activities, a movie was shot inside the reactor building during the investigation of the primary containment vessel by applying photogrammetry, which is one of the methods for three-dimensional (3D) reconstruction from images, to the images from this movie, it is feasible to perform 3D reconstruction of the environment around the primary containment vessel. However, the images from this movie may not be suitable for 3D reconstruction because they were shot remotely by robots owing to limited illumination, high-dose environments, etc. Moreover, photogrammetry has the disadvantage of easily changing 3D reconstruction results by simply changing the shooting conditions. Therefore, this study investigated the accuracy of the 3D reconstruction results obtained by photogrammetry with changes in the camera angle of view under shooting conditions. In particular, we adopted 3D computer graphics software to simulate shooting target objects for 3D reconstruction in a dark environment while illuminating them with light for application in decommissioning activities. The experimental results obtained by applying artificial images generated by simulation to the photogrammetry method showed that more accurate 3D reconstruction results can be obtained when the camera angle of view is neither too wide nor too narrow when the target objects are shot and surrounded. However, the results showed that the accuracy of the obtained results is low during linear trajectory shooting when the camera angle of view is wide.
今渕 貴志; 川端 邦明
Proceedings of 2024 IEEE/SICE International Symposium on System Integration (SII2024) (Internet), p.141 - 146, 2024/01
This paper describes a method for volumetric-based semantic 3D modeling from 3D point cloud obtained in a plant environment. In order to calculate a radiation dose distribution of the workspace in decommissioning, the shape, arrangement, materials, and thicknesses of structures are essentially required in addition to dose values. However, it is costly to create such enriched 3D models from 3D point cloud. In this study, we propose a method to create 3D models with structural category and material thickness by combining 2D image-based deep learning and volumetric reconstruction method. To discriminate structures, structural category labels are predicted by a pre-trained 2D semantic segmentation network on projected image created from 3D point cloud. Then, a triangular mesh is generated from the integrated Truncated Signed Distance Function (TSDF) according to prediction labels. In addition, we optimize the TSDF thickness assignment function to reduce surface distance error. Our evaluation reports thickness and surface distance errors when generating meshes with three different structural categories in a mock-up plant environment.
馬場 啓多*; 渡部 有隆*; 中村 啓太*; 松本 拓; 羽成 敏秀; 川端 邦明
Proceedings of 29th International Symposium on Artificial Life and Robotics (AROB 29th 2024) (Internet), p.751 - 756, 2024/01
This study proposes a partial-to-partial point cloud registration method based on estimated parameters in photogrammetry and QR code. Some research and development on Generating a 3D map of the workspace by photogrammetric methods have been proposed for the decommissioning work at the Fukushima Daiichi Nuclear Power Plant. Photogrammetry is a method for 3D reconstruction of the location and shape of target objects from many images, and the processing time depends on the number of images. Considering the reconstruction of a large area, the number of images increases, and processing time also increases significantly. To reduce such computational time, this study considers applying SfM-MVS (Structure from Motion and Multi-View Stereo), which is one of the photogrammetry methods, to each segmented image group, aligning each obtained result, integrating them, and creating a model of the entire space. This alignment is called partial-to-partial registration and it is difficult to find the correspondence points for registration. Therefore, we place markers such as QR codes in the target reconstruction space to make it easy to find the correspondence points. We adopt the QR code as a 2D code because it is easy to reconstruct by photogrammetry. In this paper, we discuss the validity of this approach by comparing it with the integrated model using all images applying SfM-MVS. We verify the validation of the proposed method by simulation due to the large number of images and the ease of modifying the environment. The experiment about varying the number of image divisions shows that the reconstruction result from all images is more accurate than the integrated result. However, all of these models have high reconstruction accuracy. Moreover, the accuracy of the integrated model does not depend on the number of divisions.
亀割 隆世*; 藤島 裕典*; 川端 邦明; 鈴木 健太; 坂上 憲光*; 武村 史朗*; 高橋 悟*
Proceedings of the IUTAM Symposium on Optimal Guidance and Control for Autonomous Systems 2023 (IUTAM Bookseries No.40), p.85 - 101, 2024/01
The purpose of this paper is to construct an ocean simulator that is useful for training the operation of underwater robots, as mentioned above, and to effectively utilize actual seafloor observation data to measure the seafloor. The proposed ocean simulator can be made more similar to actual ocean current conditions by adding a physical engine, fluid resistance, virtual currents, etc. The simulator software is based on Choreonoid, an integrated software for robot development, to achieve high scalability. Furthermore, by installing Fluid Dynamics Plugin, the underwater behavior of the ROV can be reproduced.
松本 拓; 羽成 敏秀; 川端 邦明; 八代 大*; 中村 啓太*
Proceedings of 2023 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2023) (Internet), 7 Pages, 2023/12
This paper describes an automatic system that performs three-dimensional (3D) modeling from image sequences acquired from a camera during a survey to understand the state of the environment sequentially. The developed system sequentially generates local 3D models from image sequences acquired from a camera by the Structure from Motion and Multi-View Stereo (SfM-MVS) and integrates the models. This system, consisting of a camera, a computer, and storage, handles streaming, image acquisition, 3D modeling, and integration processes. The system is designed to perform each process in parallel while performing image acquisition. Local 3D models are integrated based on the similarity of camera trajectories, which correspond to overlapped images in each sequence, estimated from SfM. Our experiments verified the operation of the developed system from the image acquisition to the integration of local 3D models in two cases. Consequently, we confirmed that an integrated model could be generated by automatically executing each process in the system through experiments.
秋山 陽一; 柴沼 蒼; 柳澤 憲一*; 山田 大地; 鈴木 健太; 吉田 萌夏; 大野 貴裕; 川端 邦明; 渡辺 夏帆; 森本 恭一; et al.
JAEA-Review 2023-015, 60 Pages, 2023/09
JAEA-Review-2023-015.pdf:4.78MB
楢葉遠隔技術開発センターは、東京電力ホールディングス株式会社が実施する福島第一原子力発電所の廃炉作業に資するため、遠隔操作機器・装置による廃炉作業の実証試験・要素試験が実施できる施設・設備を有している。2021年度は84件の施設利用を支援し、福島第一原子力発電所廃炉作業等に貢献した。また、福島第一原子力発電所の廃炉・除染に携わる事業者、災害対応分野においてロボット技術等を必要としている事業者との技術マッチングの機会として開催された廃炉・災害対応ロボット関連技術展示実演会に出展し、地域活性化・福島県の産業復興に協力した。さらに、第6回廃炉創造ロボコンや国際原子力人材育成イニシアチブ事業等の支援を通じて、長期にわたる福島第一原子力発電所の廃炉関連業務を担う次世代の人材育成に貢献した。新たな取組みとして、楢葉町教育委員会が実施している「ならはっ子こども教室」への協力として、楢葉町小学生を対象とした遠隔ロボット操作及びVRの体験会を実施し、地域教育活動に貢献した。本報告書は、2021年度における楢葉遠隔技術開発センターの施設・設備の整備・利用状況およびそれに係る取組み、遠隔基盤技術の開発状況、緊急時対応遠隔操作資機材の整備・訓練等の活動状況について取りまとめたものである。
山田 大地; 渡辺 夏帆; 鈴木 壮一郎; 川端 邦明
Automation Systems, 39(464), p.88 - 92, 2023/09
東京電力ホールディングス株式会社福島第一原子力発電所(以下、FDNPS)での事故の対応のため人の活動が著しく制限される高放射線下では、遠隔操作ロボットによる作業が不可欠となっている。このように災害現場等の危険な場所では人に代わって遠隔操作ロボットによる作業が期待される。しかしながら、災害現場のように整備されていない環境においてロボットを運用することは容易ではなく、遠隔操作ロボットにより何がどこまでできるのか(性能)を把握し、現場の状況や要求される作業に足して適したロボットを選定することが求められる。そのために、まずは遠隔操作ロボットの性能を評価する方法が必要となる。このような背景から、われわれはロボット等遠隔操作機材の試験のための設備を整備しており、また、FDNPSでの遠隔操作作業の経験を参考に原子力災害対応において遠隔操作ロボットに求められる要素的な動作を分析し、その要素的な動作に対する性能を定量的に評価する試験法の開発に取り組んでいる。本稿では、この原子力災害対応ロボットのための性能評価方法の開発について紹介する。
羽成 敏秀; 川端 邦明; 中村 啓太*
Proceedings of 22nd World Congress of the International Federation of Automatic Control (IFAC 2023) (Internet), p.11597 - 11602, 2023/07
本論文では、時系列画像に基づく立体復元の計算効率を向上させるための多峰性検出による画像選択手法について述べる。立体復元にかかる計算時間を低減するためには、時系列画像から適切な画像を選択する必要がある。そのため、画像選択過程において統計的な検定による多峰性検出を導入し、カメラから取得した画像間のオプティカルフローに基づく変位の健全性評価に適用した。その結果、立体復元の計算時間を低減するために、時系列画像から適した画像を抽出可能であることが示唆された。このことから、提案手法によって選択された画像群は、立体復元計算の効率的な実行に寄与できることを確認した。
松本 拓; 羽成 敏秀; 川端 邦明; 八代 大*; 中村 啓太*
Proceedings of 22nd World Congress of the International Federation of Automatic Control (IFAC 2023) (Internet), p.12107 - 12112, 2023/07
This paper describes a method that integrates Three-Dimensional (3D) environment models reconstructed from image sequences to reduce the computation time of 3D environment modeling that estimates camera poses and simultaneously reconstructs a 3D environment model from images based on photogrammetry. However, 3D environment modeling is time-consuming when using many images because it finds correspondence points between them by feature matching. Therefore, we assume that the computation time is reduced by reconstructing 3D environment models from image sequences divided from an image sequence because the number of images used in 3D environment modeling becomes less. However, it is difficult to integrate the 3D environment models because the scale between them may not be the same, and overlapping regions between 3D environment models are small for integrating the models. In this paper, we propose a method that integrates 3D environment models based on camera trajectories corresponding to overlapped images between image sequences used in 3D environment modeling. To integrate them, transformation parameters are calculated from poses of camera trajectories between 3D environment models. After that, the transformed camera trajectory is aligned using coarse and fine registration. Consequently, compared with 3D environment modeling that processes an image sequence in batch, the proposed method could reduce the computation time and reconstruct a comparable integrated model.
今渕 貴志; 川端 邦明
Proceedings of 20th International Conference on Ubiquitous Robots (UR 2023), p.632 - 633, 2023/06
This paper describes a feasibility study of a deep learning-based structure discrimination using data sources measured by different sensor from the sensor used when training the network for automatic creation of 3D spatial information in working environment for decommissioning. In previous work, we have developed a method for estimating geometrical shape regions and category information of structures from high-density 3D point cloud data measured in nuclear facilities. In this paper, we report the discrimination accuracy on low-density 3D point cloud data measured in a testing plant environment using the discriminator trained on high-density and high-precision 3D point cloud data measured in the same space. In addition to this, we verify the improvement of accuracy by removing noise on the surface of the structure caused by the sensor's measurement error range.
山田 大地; 阿部 浩之*; 大金 一二*; 川端 邦明
ROBOMECH Journal (Internet), 10, p.13_1 - 13_8, 2023/06
Unmand aircraft system (UAS)産業は将来の大きな発展が期待されている。しかし、UASによるサービスが提供される場所や場面においてUASがどの程度の性能を発揮できるかについて議論することは難しい。そこで、屋内などのGlobal Navigation Satellite System (GNSS)による測位が参照できない環境において、UASのユーザなど技術的な専門知識のない人にもUASの性能の理解が容易で、UAS間の性能の比較ができる性能評価およびその評価法を研究開発した。本研究開発では、UASメーカーやユーザーとデモやディスカッションを行い、その意見を取り入れながら評価法の改善を繰り返し実施した。また、評価法によりUASの性能の比較が可能であることを実験によって確認した。
