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A 2D simulation in Pygame of the paper "Probabilistic roadmaps for path planning in high-dimensional configuration spaces" by L.E. Kavraki, P. Svestka, J.-C. Latombe, and M.H. Overmars.

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Probabilistic Roadmaps

animated

Description

A 2D simulation in the framework Pygame of the paper Probabilistic roadmaps for path planning in high-dimensional configuration spaces. The environment has 2 non-convex obstacles that can be used or not. It also uses the A* algorithm to find the more suitable an optimal path from the forest created by the PRM.

Usage

usage: PRM.py [-h] [-o | --obstacles | --no-obstacles] [-init  [...]]
              [-goal  [...]]
              [-srn | --show_random_nodes | --no-show_random_nodes] [-n] [-k]

Implements the PRM algorithm for path planning.

options:
  -h, --help            show this help message and exit
  -o, --obstacles, --no-obstacles
                        Obstacles on the map
  -init  [ ...], --x_init  [ ...]
                        Initial node position in X and Y respectively
  -goal  [ ...], --x_goal  [ ...]
                        Goal node position in X and Y respectively
  -srn, --show_random_nodes, --no-show_random_nodes
                        Show random nodes on screen
  -n , --nodes          Number of nodes to put in the roadmap
  -k , --k_nearest      Number of the closest neighbors to examine for each
                        configuration

Examples

Generate obstacles in the map and show the random nodes $\mathbf{x_{\mathit{rand}}}$

python3 PRM.py --obstacles --show_random_nodes

No obstacles, initial configuration $\mathbf{x_{\mathit{init}}} = (300, 300)$ and goal configuration $\mathbf{x_{\mathit{goal}}} = (50, 100)$

python3 PRM.py --no-obstacles --x_init 300, 300 --x_goal 50, 100

License

MIT License

Copyright (c) [2022] [Angelo Espinoza]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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A 2D simulation in Pygame of the paper "Probabilistic roadmaps for path planning in high-dimensional configuration spaces" by L.E. Kavraki, P. Svestka, J.-C. Latombe, and M.H. Overmars.

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