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Dynamic Particle Swarm Optimization Algorithm for Intelligent Mobile Robot Path Finding System

Rawaa Jawad, Eyad I Abbas, Sundus D Hasan

This study investigate application for Particle Swarm Optimization (PSO) to robot mobility problem to determine a shortest path possible with minimum time required to move from starting point to target point in ergonomics with obstacles. In this paper, algorithm is used to chart global path. A proposed algorithm reads ergonomics expressed by network model and creates an ideal collision-free path. Simulation studies have proven a effectiveness for proposed algorithm to chart path for mobile robot. This study showed how to optimize a path planning for an intelligent mobile robot by making optimal use for a PSO technology work environment with obstacles. A basis for this study is societal behavior Birds flow and raise fish. This concept is powered by Swarm intelligence, and is one for a famous research fields in a field for computational swarm intelligence, as a particle swarm improvement algorithm (PSO). Important notes have been made portable robots are greatly affect by path finding problem and solution is being developed for How to solve this problem., this study suggests a good solution that can produce high-quality and effective portable robots. PSO technology has been adapted to provide effective solution to path finding problems.