Dual-stage Planner for Autonomous Radioactive Source Localization in Unknown Environments

This paper describes a novel approach for the autonomous localization of radioactive sources in complex unknown environments. The approach contains two stages: a source tracking stage for detailed source term estimation (STE) with recent measurements, and a relocation stage for transiting the robot to another sub-area after the current one is ruled out. The STE algorithm in conjunction with the convex polyhedrons extracted from the environment enables our method to be deployed in realistic scenarios with complex obstacles, which are often unfeasible for existing methods. The source confirmation algorithm in the relocation stage considerably accelerates the overall processing, improving the time efficiency in finding the radioactive sources. In both simulations and experiments, this approach is able to precisely localize at the success rate of 90% within an average of less than 13 measurements in 7 different environments, which is impressive when compared to the traditional STE which can hardly achieve an accurate estimation in most cases.