Takuya Kishimoto, Hanwool Woo, Ren Komatsu, Yusuke Tamura, Hideki Tomita, Kenji Shimazoe, Atsushi Yamashita, Hajime Asama: Path Planning for Localization of Radiation Sources Based on Principal Component Analysis, Applied Sciences, Vol.11, No.10, 4707, 2021. doi:10.3390/app11104707
In this paper, we propose a path planning method for the localization of radiation sources using a mobile robot equipped with an imaging gamma-ray detector, which has a field of view in all directions. The ability to detect and localize radiation sources is essential for ensuring nuclear safety, security, and surveillance. To enable the autonomous localization of radiation sources, the robot must have the ability to automatically determine the next location for gamma ray measurement instead of following a predefined path. The number of incident events is approximated to be the squared inverse proportional to the distance between the radiation source and the detector. Therefore, the closer the distance to the source, the shorter the time required to obtain the same radiation counts measured by the detector. Hence, the proposed method is designed to reduce this distance to a position where a sufficient number of gamma-ray events can be obtained; then, a path to surround the radiation sources is generated. The proposed method generates this path by performing principal component analysis based on the results obtained from previous measurements. Both simulations and actual experiments demonstrate that the proposed method can automatically generate a measurement path and accurately localize radiation sources.
Feiyun Cong, Yusuke Tamura, Kenji Shimazoe, Hiroyuki Takahashi, Jun Ota, and Shuiguang Tong: Radioactive Source Recognition with Moving Compton Camera Imaging Robot Using Geant4, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol.953, 163108, pp.1-12, 2020. doi:10.1016/j.nima.2019.163108
Robotics is becoming increasingly important in modern engineering areas. After the big nuclear accidents in Fukushima 2011, the crossing research of nuclear and robotics draws more and more attentions. In this paper, a method for radioactive source recognition using moving Compton camera imaging robot is proposed. In order to assess the quality of the reconstructed image, a new method called Cross-section Outline at Half Maximum (COHM) is proposed for three dimensional image reconstruction precision assessments. Two experiment validations using Geant4 platform are given which include the measurement with different distances and angles respectively. The result shows that the application of Compton camera imaging robot can improve the radioactive source image reconstruction quality. Based on the result of the experiment, several preconditions and suggestions are given to improve the image reconstruction precision when we apply robot to the radioactive source recognition. The research is focused on the three dimensional image reconstruction by using Compton camera imaging robot. It can improve the radioactive source recognition precision especially for three-dimensional contour recognition. And also it can supply good reference for the robot routine planning when we apply the robot into radioactive source recognition in future.
Doyeon Kim, Hanwool Woo, Yonghoon Ji, Yusuke Tamura, Atsushi Yamashita, Hajime Asama: 3D Radiation Imaging Using Mobile Robot Equipped with Radiation Detector, Proceedings of the 2017 IEEE/SICE International Symposium on System Integration, pp.444-449, 2017. doi:10.1109/SII.2017.8279253
This paper presents a novel scheme for the three-dimensional (3D) reconstruction of radiation source distribution by using multiple viewpoint of detector. Detecting and localizing radiation source are required for nuclear safety, security, and surveillance when considering exposure to radiation. In such cases, 3D reconstructed information would greatly contribute to a better understanding of the spatial relation between radiation sources and a surrounding environment. Considering contamination of radiation for human, we used a mobile robot equipped with a detector because it is suitable to measure a radiation in multiple viewpoint. We assume that trajectory of the mobile robot with the detector (i.e., pose of the detector) is estimated by simultaneous localization and mapping (SLAM) scheme. Therefore, 3D radiation source distribution can be reconstructed by utilizing maximum likelihood expectation maximization (MLEM) method, which performs optimization based on all measured data and estimated detector poses. The result of the simulation experiment demonstrated that the proposed framework can accurately perform 3D reconstruction of radiation image in the indoor environment.