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A* Pathfinding Algorithm

Steps to run

  1. Clone repo and run example script python example.py

  2. Adjust start and goal parameters in the example.py script to try different paths

This was partially done in Udacity's Intro to Self Driving Car Nanodegree. I ported my solution to run locally and rewrote the visualization logic to reduce dependencies.

The heuristic being used is Euclidean distance calculated by h(n) = sqrt((x1 - x2)**2 + (y1 - y2)**2)

Below is an example of the generated network with the shortest path between 8 and 35 highlighted Shortest path between node 8 and 35