Path Planning Using Particle Swarm Optimization with Linear Crossover Operator

The problem which is gaining popularity these days is path planning problem with multipleobstacles. Its main purpose is to find a collision free path from an initial position to a goal position inan environment with obstacles. One major challenge in this area is to design effective algorithms thatcalculate the shortest path between starting point to goal point and avoid obstacles. In this paper a newmethod is proposed by using the properties of PSO and linear crossover operator of genetic algorithmand named the proposed methodology as PSO with Linear crossover algorithm. In this paper pathplanning problem is solved by using PSO with linear crossover algorithm. The objective functiondefined is novel in nature. The constraints are defied such that path generated does not collide withthe obstacles. Two constraints are defined i.e. point repair penalty and path repair penalty. To test theefficiency of proposed PSO with linear crossover algorithm results are compared with particle swarmoptimization (PSO) and differential evolution (DE). From the experimental result it is clear that theproposed method PSO with linear crossover gives better path or optimal path.