Path Planning for Mobile Robot Based on ACA-GA

Abstract

Path planning for mobile robot is a kernel problem in the robot technology area, with the characteristics of complexity, binding and nonlinearity. On account of global path planning for mobile robot in static environment, this paper discussed a method of combining ant colony algorithm and genetic algorithm. After completing a cycle of ant colony algorithm, two paths ants walked were randomly selected, and these two paths were further optimized genetically on the basis of certain crossover rate, if more optimal paths were obtained, the pheromone would be released in the more optimal paths, by this method the diversity of solution could be increased and solution speed be improved. The simulation result has verified the effectiveness of the proposed method.