Abstract

The evolution of path-planning algorithms has been remarkable in recent years. These algorithms are widely used in both industrial and everyday settings. They play a major role in the successful navigation of robots, as well as in games and other applications. Path planning algorithms can provide optimal solutions even in complex, high-dimensional environments. Among all the available path planning algorithms, the most widely used are RRT-Star and its variants, including RRT-Star Connect, RRT-Star Smart, Bidirectional RRT-Star, TG RRT-Star, and others. This paper presents a detailed study of these algorithms, taking into account various metrics for performance evaluation and comparing the results in different environments. The study presents a discussion on the classification of path-planning algorithms based on the environment, the nature of the algorithm, and its completeness. It also delves into the hierarchy of RRT-based algorithms to comprehend the improvements made to the algorithms and the important characteristics of each algorithm that is being followed.