Path planning for a mobile robot using genetic algorithms

This paper presents a new algorithm for global path planning to a goal for a mobile robot using Genetic Algorithm (GA). A genetic algorithm is used to find the optimal path for a mobile robot to move in a static environment expressed by a map with nodes and links. Locations of target and obstacles to find an optimal path are given in an environment that is a 2-D workplace. Each via point (landmark) in the net is a gene which is represented using binary code. The number of genes in one chromosome is function of the number of obstacles in the map. Therefore, we used a fixed length chromosome. The generated robot path is optimal in the sense of the shortest distance. The robot has a starting point and a target point under the assumption that the robot passes each point only once or not at all. The obtained results in simulation affirmed the potential of the proposed algorithm.