Rapidly exploring random tree

Okay kiddo, imagine that you want to find a hidden treasure in a very big jungle. But you don't know where it is. One way to find it is to randomly explore different paths in the jungle, hoping to stumble upon the treasure.

Rapidly exploring random tree (RRT) is a technique that uses the same idea to solve complex problems in computer science, like finding the shortest path between two points.

Imagine that you have a big map with obstacles and you want to find the shortest path from point A to point B. RRT starts by placing point A on the map and then randomly putting another point nearby. The two points are connected by a line.

Next, RRT randomly selects another point and checks if it's too close to an obstacle. If it is, it tries again with a different point. If the new point is not too close to an obstacle, it connects it with the nearest point already on the map.

This process repeats many times, forming a tree-like structure with branches of connected points. Eventually, a point near point B will be added to the tree, and you can trace the path from A to B by following the connected lines from start to finish.

RRT is very smart because it only generates points where they are needed and avoids wasting time exploring dead-ends or paths that are blocked by obstacles. RRT is used in many applications, like robotics, computer graphics, and navigation systems to find the best solution for complicated problems.