Comparison Of Gsa, Sa And Pso Based Intelligent Controllers For Path Planning Of Mobile Robot In Unknown Environment

摘要

Now-a-days autonomous mobile robots have found<br> applications in diverse fields. An autonomous robot system must be<br> able to behave in an intelligent manner to deal with complex and<br> changing environment. This work proposes the performance of path<br> planning and navigation of autonomous mobile robot using<br> Gravitational Search Algorithm (GSA), Simulated Annealing (SA)<br> and Particle Swarm optimization (PSO) based intelligent controllers<br> in an unstructured environment. The approach not only finds a valid<br> collision free path but also optimal one. The main aim of the work is<br> to minimize the length of the path and duration of travel from a<br> starting point to a target while moving in an unknown environment<br> with obstacles without collision. Finally, a comparison is made<br> between the three controllers, it is found that the path length and time<br> duration made by the robot using GSA is better than SA and PSO<br> based controllers for the same work.