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SimplePlanner

Code used to generate some classical planning algorithm legends for my master's thesis

Overview

There are two types of planning algorithms in this repo, namely, Graph Search Planning Algorithm (BFS, DFS, Greedy, A*) and Sampling-based Planning Algorithm (PRM, RRT):

Algorithm ScreenShot
Breadth First Search (BFS) BFS
Depth First Search (DFS) DFS
Greedy Search (Greedy) Greedy
A* A*
Probabilistic Roadmap (PRM) PRM
Rapidly-Exploring Random Trees (RRT) RRT

Usage

Graph Search Planning Algorithms (BFS, DFS, Greedy, A*)

python3 app.py --num_horizontal_grid 40 --num_vertical_grid 40 --radius 4 --algorithm [BFS, DFS, Greedy, AStar]
  • --num_horizontal_grid: the number of horizontal grid
  • --num_vertical_grid: the number of vertical grid
  • --radius: the radius of the start and goal dots
  • --algorithm: the planning algorithm, could be one of BFS, DFS, Greedy and AStar

Sampling-based Planning Algorithms (PRM, RRT)

# For PRM
python3 app.py --radius 4 --algorithm PRM --num_node 1000 --num_nearest 4

# For RRT
python3 app.py --radius 4 --algorithm RRT --num_node 1000 --step_size 20
  • --radius: the radius of the start and goal block
  • --algorithm: the planning algorithm, could be one of PRM and RRT
  • --num_node: the number of sampled nodes in the Roadmap or Tree
  • --num_nearest: the number of nearest neighbours used to construct the roadmap
  • --step_size: the step size used to extend the tree

Setting Start and Goal Position

  • Start Position: Mouse Double Left Click (Green)
  • Goal Position: Mouse Double Right Click (Red)

Note: You can also edit the canvas.json file to customized the environment.