The State of Art on Navigational Algorithm for Path Optimization of a Mobile Robot

Mobile robots are vital for automation industries, surveillance and mapping, hazardous operation like nuclear plants, landmine detection etc. The path of such robots is controlled by a navigational algorithm. Several algorithm have been proposed and tried out for navigation of an autonomous mobile robot (AMR) around the globe .Some of these determine the path which is feasible to reach the destination without collision, while other also tries to optimize .Key parameters of the navigation are distance and time (either or both) to reach the destination or cost of reaching the destination. The prevalent algorithm have used various technique like fuzzy logic, genetic algorithm, artificial neural network, dynamic programming, potential field method, bug algorithm, ant colony optimization etc. Many others have developed the specific algorithms in evolutionary manner stage by stage through various trials. This also includes a number of heuristic based algorithms. This article describes the important features of the current navigational algorithm for optimizing the path of an autonomous mobile robot (AMR).The relative merits and demerits and challenges of each of these have been identified with a view to obtaining a methodology of overcoming the challenges. Keywords— Autonomous mobile robot, Fuzzy logic, Genetic Algorithm, Artificial neural network, Robot motion Planning ——————————  —————————