In this study, we develop a search technique involving heterogeneous robots to achieve a rapid and accurate search for a lost radioactive source by effectively utilizing radiation data. The system includes robots with different levels of radiation resistance. Two fixed robots with lower radiation resistance are positioned at the edge of the environment to collect low-value radiation data and apply a maximum likelihood estimation algorithm based on the natural gradient (NG-MLE) for localization. Concurrently, a mobile robot with high radiation resistance enters the warning area to collect high-value radiation data, and the localization of the radioactive source is performed based on particle filtering and prior information obtained from the fixed robots. The movement of the mobile robot is directed by a decision-making algorithm based on Fisher information distance (FID). Simulation results show that the proposed algorithm achieves higher localization accuracy and requires fewer radiation detections.
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