3D reconstruction based on grouping similar structures for images acquired in the Fukushima Daiichi Nuclear Power Station

Imabuchi, Takashi; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of 2025 IEEE/SICE International Symposium on System Integration (SII2025), p.1416 - 1421, 2025/01

Feasibility study on noise reduction from images using deep learning to improve spatial awareness in remote operation

Tanifuji, Yuta; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of International Topical Workshop on Fukushima Decommissioning Research 2024 (FDR2024) (Internet), 3 Pages, 2024/10

Investigation of the influence of the magnitude of camera vibration on 3D reconstruction results by photogrammetry based on simulation

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

Proceedings of 2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2024), p.7 - 8, 2024/07

Photogrammetry is a technique for 3D reconstruction of target objects from multiple images shot of the object. In the case of actual photography, the object may not be reconstructed due to the inability to shoot images suitable for photogrammetry because of vibration in the camera's angle of view of the object. Therefore, we implement this vibration by using random numbers and verify the influence of the magnitude of the vibration on the reconstruction result obtained by photogrammetry. The verification results show the relationship between the magnitude of the vibration and the success rate of 3D reconstruction.

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

https://doi.org/10.1109/LRA.2024.3366022

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.

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 29th 2024) (Internet), p.751 - 756, 2024/01

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

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

https://doi.org/10.1007/s10015-022-00835-x

Verification for scaling 3D reconstruction result from images based on 2D code size in linear trajectory shooting

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

Proceedings of 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2022), p.1497 - 1498, 2022/07

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.

An Image selection method from image sequence collected by remotely operated robot for efficient 3D reconstruction

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

Proceedings of International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP 2020) (Internet), p.242 - 245, 2020/02

In this paper, we propose an image selection method to realize efficient three-dimensional (3D) reconstruction from image sequence collected by a remotely operated robot. The proposed method is to select adequate images for reconstruction computation based on optical flow measures. We confirmed that the proposed method can select adequate images for 3D reconstruction from the image sequence recorded by the remotely operated robot that is commanded stop-and-go motions. As a result, we demonstrated a 3D reconstruction could be performed efficiently with relatively few images that were selected by the proposed method.