Genetic Algorithm-Based Path Planning for Autonomous Mobile Robots

Abstract

In this paper, a Genetic Algorithm is used to solve the path planning problem for autonomous mobile robots in static environments. The goal of the path planning problem is to find a valid and practical path between two points while avoiding obstacles and optimizing a number of criteria including path length, safety, and distance from obstacles. A quality function is proposed to evaluate the optimization approach for different scenarios. Experimental results show that enhanced solutions can be achieved in less time using optimal values of the search algorithm parameters.