A Comparison Particle Filter for Searching a Radiation Source in Real and Simulated World

Abstract

In this paper, we are focusing on comparing solutionsfor localizing an unknown radiation source in both aGazebo simulator and the real world. A proper simulation ofthe environment, sensors, and radiation source can significantlyreduce the development time of robotic algorithms. We proposeda simple sampling importance resampling (SIR) particle filter.To verify its effectiveness and similarities, we first tested thealgorithm’s performance in the real world and then in the Gazebosimulator. In experiment, we used a 2-inch NaI(Tl) radiationdetector and radiation source Cesium 137 with an activity of 330Mbq. We compared the algorithm process using the evolution ofinformation entropy, variance, and Kullback-Leibler divergence.The proposed metrics demonstrated the similarity between thesimulator and the real world, providing valuable insights toimprove and facilitate further development of radiation searchand mapping algorithms.