To address the problems of inaccurate dose rate and long-period measurement, this paper presents a nuclear radiation detector with the function of directional determination, as well as the corresponding Bayesian-based strength estimation method. Firstly, a vehicle-mounted radiation detector with large measurement range is designed, together with the steering mechanism and size-differentiated shielding shell, completing the ultra-wide measurement range of 0.15μGy/h~500Gy/h and the precise directional aiming functions. Enlightened by the characteristics of conjugated Gamma distribution, the radiation strength estimation method is established in an iterative manner. By comparing and analyzing the convergence properties and prediction efficiency under different shape parameters γ and scale parameters β, the selection criteria for initial model parameters is clarified. Finally, the proposed nuclear detector and estimation method are applied in the actual radiation source searching task, verifying the real-time, effectiveness, and accuracy of the overall radiation source detection system. The experimental results show that, the measurement method based on conjugated distribution theory can significantly reduce the number of estimated iterations to less than 15 steps, and improve the accuracy of the directional aiming function, ensuring the ability of on-line exploitation and exploration for the mobile system.
The unmanned system is always employed in the uncontrolled radiation source accidents, tackling with geometric field mapping, obstacle avoidance exploration and radiation sources localization simultaneously. To balance the multiple subtasks, a novel source seeking and exploration strategy is proposed in this paper. Firstly, the geometric metric map and radioactive topology map are constructed respectively, while the evaluation functions are established to merge above both maps into the hybrid costmap. Additionally, the RRT* structure is introduced into the path planning module, leading to the capabilities of full-map expansion and multi-source exploitation. By combining the costmap with RRT* structure, the topological paths which satisfy source seeking and map exploration can be generated in the cluttered environment. Experimental results verify the effectiveness of the multi-task path planner, taking into account both multisource exploitation and environment exploration in an online manner.
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