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.2019.163108abstract
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.2017.8279253abstract
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.