Radiation Mapping based on DFS and Gaussian Process Regression

This paper proposes a method for the reconstruction of radiological maps. Using a mobile robot equipped with a nuclear radiation detector, the radiation map is drawn in the following steps. Firstly, the target area is modeled using a grid-based method, and based on the distribution of obstacles, the target area is divided into several cells. The robot performs zigzag movements within each cell, and it traverses the entire target area according to the traversal sequence determined by Depth-First Search (DFS) for each cell. Finally, based on the radiation information collected by the robot along the path, the radiation field is reconstructed using Gaussian Process Regression. Computer simulation experiments demonstrate the effectiveness of this method in visualizing the nuclear radiation environment. This approach holds promise for application in radiation mapping for unmanned lunar rovers on the lunar surface.