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2D Implementation of the Phi* path planning algorithm, using Python, Numpy and Matplotlib

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Phi* 2D

2D Implementation of the paper by Nash and Koenig Incremental Phi star, incremental any-angle path planning on grids using Python, Numpy and Matplotlib.

To run the simulation use:

# Run the simulation with the Phi* path planning algorithm
python phi_star.py


# Run the simulation with the Theta* path planning algorithm
python theta_star.py

To configure the setup of the simulation, you can edit the config.py file.

Performance analysis with Theta*

Theta*: Daniel, Nash, "Theta star, Any-angle path planning on grids"

Time comparison

# Size Obstacle size Offset Theta* Theta* - Replanning (end) Phi* Phi* - Replanning (mid) Phi* - Replanning (end)
1 (100, 100) 6 0 0.04888 0.05731 0.7533 0.03627 0.03152
2 (500, 500) 6 0 0.5551 0.5386 0.7062 0.5521 0.3449
3 (1000, 1000) 20 0 2.578 2.797
4 (5000, 5000) 20 0 142.50 210.18

Length comparison

# Size Obstacle size Offset Theta* Phi*
1 (30, 30) 6 0 42.71 44.01

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2D Implementation of the Phi* path planning algorithm, using Python, Numpy and Matplotlib

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