Enhanced GA for Mobile Robot Path Planning Based on Links among Distributed Nodes


In this paper, we propose an Enhanced Genetic Algorithm (EGA) to find the optimal path for a mobile robot. The workspace of the mobile robot is assumed to be of known environment with many static obstacles. The space of environment is divided into equally quarters by projection of a grid of specified distance on the environment space. Each quarter represents a node in the workspace. Moreover, each node has assigned by a unique number. So, all these nodes are distributed uniformly in the workspace. Each node may link to another node by straight line unless this line crosses one or more obstacles. New operator named Validation of Links operator introduces here to check all valid links between any two nodes. The GA operators adjusted and enhanced to suit the path planning problem and further more we develop new other operators to increase the efficiency of the algorithm. Simulation studies are carried out to verify and validate the effectiveness of the proposed algorithm.