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RRT Algorithm (Rapidly-exploring Random Tree)

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Demo

See this Jupyter notebook for an example of RRT in action:

colab

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Example of RRT

RRT is a sampling-based method used often in high-dimensional spaces. It's particularly useful in cases where the exact representation of obstacles is unknown or hard to compute.

Basics of RRT

  1. Initialize the tree with a starting node.
  2. For a predetermined number of iterations:
    • Select a random point in the space.
    • Find the closest node in the tree to the random point.
    • Add a new node to the tree that's a set distance towards the random point from the closest node.
    • If the new node is close enough to the goal, connect it and terminate.