Path-finding algorithms are used in navigation systems to guide robots from one location to another. These algorithms have become more efficient in recent years, especially in complex environments. However, they may struggle with maps with the highest degree of complexity, such as mazes. One widely used algorithm in navigation systems is the RRT algorithm, but it is not perfect. Due to its limitations, a new algorithm has been proposed in a research paper. This new algorithm improves upon RRT by introducing additional functions for sampling and optimizing the path. The paper also suggests a method for smoothing the path using the Reeds–Shepp path planning approach. This approach breaks down the path into multiple segments of quickly followed commands rather than a complex curve. These advancements in path-finding algorithms are significant and could lead to more efficient navigation systems, especially in complex environments.