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A prototype system based on a combination of 4π sensitive gamma imaging and simultaneous localization and mapping (SLAM) was developed to find unknown radiation source(s) rapidly. The system consisted of a spherical visible camera, a three-dimensional light detection and ranging, a CdTe pixel array detector for 4π gamma imaging, a portable battery, and a control laptop personal computer; these were mounted on an unmanned vehicle. In a search area of 16 × 16 m2 with a height of 3 m, the prototype system successfully demonstrated the finding of a 137Cs point source with an activity of 0.67 MBq in the surrounding thin walls. [ABSTRACT FROM AUTHOR]

We developed a path-planning system for radiation source identification devices using 4π gamma imaging. The estimated source location and activity were calculated by an integrated simulation model by using 4π gamma images at multiple measurement positions. Using these calculated values, a prediction model to estimate the probability of identification at the next measurement position was created by via random forest analysis. The path-planning system based on the prediction model was verified by integrated simulation and experiment for a 137Cs point source. The results showed that 137Cs point sources were identified using the few measurement positions suggested by the path-planning system. [ABSTRACT FROM AUTHOR]

The Fukushima Daiichi nuclear disaster occurred during the Great East Japan Earthquake. Inside the reactor, materials with high radioactivity were scattered entirely, leading to a severe condition that restricted the number of measurement spots where the detector could be used. We propose a new system based on a plane model that uses fewer measurement spots and causes fewer estimation errors. We estimated the radiation source distribution using the maximum-likelihood estimation method optimized by gradient descent. Consequently, it was found that the proposed system, showed fewer errors than the previous system with a limited number of measurement spots. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]