Path Planning Algorithms: An Evaluation of Five Rapidly Exploring Random Tree Methods

Abstract

Path planning is one element of mobile robot navigation. It helps a robot arrive at its destination safely by defining its route from the start to the end locations. The Rapidly Exploring Random Tree (RRT) algorithm is a frequently employed type of path planning technique because it is uncomplicated, even though it does not come up with the optimal route. For this reason, variations of RRT algorithms have been developed to improve its effectiveness. This paper evaluates the performance of five variations of RRT algorithms. These include the RRT, Rapidly Exploring Random Tree Star (RRT*), Informed RRT*, Linear Quadratic Regulator Rapidly Exploring Random Tree Star (LQR RRT*), and the Batch Informed Tree Star (BIT*).