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A Location Algorithm for Orphan Radioactive Source


 In order to reduce the harm to public safety caused by the loss of radioactive sources. A source searching method is proposed to locate orphan gamma source in the environment with obstacles and radiation shielding. The method is divided into two parts: predicting the probability of a radioactive source by Gaussian process regression (GPR) and path planning for the mobile robot using the probabilistic roadmap (PRM) method. The mean function and covariance function of the Gaussian process need to be selected in advance and the hyperparameters are calculated in the training process. Predicted values of GPR are given in the form of Gaussian distribution, which make us able to calculate the probability that there is a radioactive source in the grid and construct a probability map to guide the robot. The path connecting the start grid to the target grid is planned by the PRM method in a very short time, the cost function of A* algorithm in the query phase controls the pattern of the robot. At the beginning of the search, the robot prefers to move to areas with more information, after data above the threshold is detected, the robot switches to the tracking mode, accesses to the radioactive source rapidly. The effectiveness of the proposed method is verified in a simulation experiment in which a 10m × 10m radiation field with five walls is simulated. The searches of gamma point source are all successfully realized in 5 different cases and compared with the total number of discrete grids, the method uses only a small part of the grid data to realize the location. Overall, the results show that the proposed method is efficient for searching and locating orphan radioactive source.