Middle Node Optimization algorithm for global optimal path planning

This paper proposes a new algorithm for solving the robot path planning problem which includes finding a path from a source to a destination subject to certain constraints. First, using the overhead view of the surroundings, a free space model is created using MAKLINK graph theory. Then Dijkstra's Algorithm is applied over the MAKLINK graph to obtain a sub-optimal path. This sub-optimal path is further optimized using the proposed Middle Node Optimization (MNO) algorithm. Using computer simulations, MNO algorithm is compared with Basic PSO (Particle Swarm Optimization), RCPSO (Random Coding PSO) and Ant Colony System (ACS) algorithms on the basis of convergence speed and the resultant optimized path lengths.