Classical Approaches for Mobile Robot Path Planning: A Review

Abstract

Robotics experts are paying close attention to robot motion planning, which has grown into a crucial job in the field of navigation. It provides a simple and effective approach to the coordination of robots in a complex environment. This article presents a review of various classical approaches employed for the path planning of mobile robots and their performance in a static grid environment. This article discusses the various methods used for disintegrating an environment. Classical approaches are classified into two categories: (a) Search-based, and (b) Sample-based. These algorithms were run on two grid environments and compared based on the time taken to discover the shortest path, the length of the path and the number of paths discovered to select the shortest among them. A* algorithm was observed to be the most optimal search-based algorithm and Fast Marching Trees was the most optimal sample-based algorithm in a static known environment.