Path Planning of Prm Based on Artificial Potential Field in Radiation Environments

Abstract

An improved probabilistic roadmap algorithm (APF-PRM) is proposed based on the combination of artificial potential fields (APF) and probabilistic roadmap algorithm (PRM) for path planning in complex static radiation environments. The entire two-dimensional dose field model of the radiation environment is constructed using bilinear interpolation based on simulation data from Geant4. The new algorithm is integrated with the A* algorithm to perform path planning in the radiation environment. In the first experimental case, a comparison with the traditional A* algorithm demonstrates that the APF-PRM algorithm achieves faster computation speed, with a 5.45-fold improvement in computation speed in the same environment compared to the A* algorithm. In the second experiment, which involves a more complex environment, the APF-PRM algorithm reduces the cumulative personnel radiation dose by 16.25% compared to the traditional PRM algorithm.

Keywords: Path planning, Nuclear radiation field, Probabilistic roadmap algorithm, APF-PRM, A* algorithm