path-planning-ode

This is my revamped code for solving the autonomous path planning problem outlined at https://www.youtube.com/watch?v=fNBrIngCJp8&t=9s

REQUIREMENTS:

-numpy -sympy -matplotlib

MODULE USAGE:

---

To initialize Path Planning Object:

pp = PathPlanningODE(
                    starting_coordinate - tuple, (-2, -2) by default
                    ending_coordinate - tuple, (12, 12) by default
                    NUM_OF_STEPS - int, 20 by default
                    )

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To create obstacles in the Path Planning field:

pp.create_obstacles(
                    NUM_OF_OBSTACLES - int, 10 by default
                    coordinates - list of tuples, None by default
                    )

    Example usage:

        To place one obstacle at (5, 5)
        pp.create_obstacles( coordinates=[(5,5)] )

        To place two obstacles, one at (1,2) the other at (3,4)
        pp.create_obstacles( coordinates=[(1,2), (3,4)] )

        To place 5 obstacles randomly
        pp.create_obstacles(5)

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To show current state of path planning problem:

pp.show_solution()

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To do one iteration of Newton's Method (calculate new path based on current path):

pp.update_path()

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To watch an animation of the ODE sovler in action (this is fun - this is where you'll see it
trying to wiggle the path around into place):

pp.animate_solver()

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To watch the 'rover' follow the current path:

pp.animate_rover()  

SAMPLE USAGE

---

import pathplanning2019 # import module

pp = PathPlanningODE() # create instance of path planning object w/ default settings

pp.create_obstacles() # create 10 randomly placed obstacles

pp.animate_solver() # animate the solution process