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Single robot path planning algorithms implemented in Python. Including heuristic search and incremental heuristic search methods. A*, PEA*, EPEA*, LPA*, D*Lite

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MortezaHagh/path-planning-py

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PathPlanning-Py

Single robot path planning algorithms implemented in Python. Including heuristic search and incremental heuristic search methods.

Incremental heuristic search methods are used for dynamic path planning with changes in the map (environment).

Methods

  • heuristic search methods

    • A* (can turn into Dijkstra by changing the heuristic function)
    • PEA*:Partial Expansion A*
    • EPEA*:Enhanced Partial Expansion A*
  • incremental heuristic searchs method (For dynamic environments and moving agents)

    • LPA*(Life Long Planning A*)
    • D*Lite

Simulations

1 2 3

Run

Run the run_auto.py at methods directory

  • AStar/run_astar.py
  • PEAStar/run_astar.py
  • EPEAStar/run_astar.py
  • LPAStar/run_lpastar.py
  • DStarLite/run_dstar_Lite.y

Settings

Settings JSON file:

zMethodHandler/Settings/settings_auto.json

Includes:

  • Model settings:

    • dist_type : distance type('euclidean' or 'manhattan')
    • adj_t_ype: connection type ('4adj' or '8adj')
    • expand_method: expansion method:
      • 'random': onlly based on distance cost
      • 'heading': based on distance and heading
  • setting_pp:

    • map_id: number of the map (see common/mode_inputs.py)

Model (MAP) - Problem definition

Check out the common/model_inputs.py file to your custom model (map). Remember to update settings_auto.json file.

Common Directory

Includes scripts used in all path planning methods.

  • create base model (map and configurations) for all methods
  • Final evaluation
  • Plotting
  • ...

Dependencies

  • python3
  • numpy
  • matplotlib

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