Using simplified swarm optimization on path planning for intelligent mobile robot

This study examined how path planning of intelligent mobile robot could be enhanced by utilizing simplified swarm optimization (SSO) in working environment with irregular obstacles. The conceptual framework of this study was driven from an inspiration of communal behavior of birds flocking and fish schooling. This conceptual framework was supported by swarm intelligence, which is one of the famous research areas in the field of computational swarm intelligence such as particle swarm optimization (PSO) algorithm. Significant observations have been made that mobile robots are significantly affected by path planning problems, and solutions are established how to tackle these problems and numerous weaknesses. Therefore, this study proposes an effective solution which can yield a high quality and efficient mobile robots. The SSO technique was adapted in order to provide an effective solution to the discussed weaknesses. The designed simulation algorithm results showed that SSO does not have assemble in the closed work interface where no path between the initial and the destination points. Obtained results show that when the particle's path gets into an obstacle area, it is automatically repositioned to an obstacle free area. Autonomy and energy efficiency within the particles are also discussed.