Genetic Algorithms for Coverage Path Planning using Mobile Robots

Abstract

Using the grid method to establish the environmental model, the map is divided into several sub-regions according to the environmental characteristics, and the connection between the sub-regions is established. Next, the Genetic Algorithm encodes all sub-regions, and the base point information between and within each region is established to obtain the optimal coverage sequence. Partial coverage is achieved in each sub-region by means of reciprocating motion, which turns the complete coverage problem into a traveling salesman problem (TSP). Finally, the Genetic Algorithm is used to conduct an experimental simulation to obtain the correlation between the fitness and the number of iterations, and obtain the optimal traversal sequence, which proves that the method is effective and feasible.