• ✨ Built to be expanded: easy to add new planners
• 🖥️ Supported on Ubuntu
• 🎌 Built with Python
• 🔎 Reactive Distributed Planners (Nonlinear Model Predictive Control, Velocity Obstacles)
• 🧭 Centralized Planners (Space-Time A*)
• 📊 Benchmark Tools (Incoming...)
• 🍻 Maintained (Incoming: Enhanced Conflict-Based Search, Local-Repair A*, Replanning RRT*...)

• Install Python (3.7.5 is the tested version)
• Install Pip: sudo apt install python3-pip
• Upgrade Pip: python3 -m pip install --upgrade pip

• Clone the repo: git clone https://github.com/apla-toolbox/pymapf
• Cd into the repo cd pymapf
• Install requirements: python3 -m pip install -r requirements.txt

• Install the package: python3 -m pip install pymapf

Launch hub switch scripts using:

• python3 scripts/switch_positions_nmpc.py
• python3 scripts/switch_positions_vel_obstacles.py (broken)

More to come...

from pymapf.decentralized import MultiAgentNMPC
from pymapf.decentralized.position import Position
import numpy as np

sim = MultiAgentNMPC()
sim.register_agent("r2d2", Position(0, 3), Position(10, 7))
sim.register_agent("bb8", Position(0, 7), Position(5, 10))
sim.register_agent("c3po", Position(10, 7), Position(5, 0))
sim.register_obstacle(2, np.pi/4, Position(0, 0))
sim.run_simulation()
sim.visualize("filename_test", 10, 10)

from pymapf.decentralized.velocity_obstacle import MultiAgentVelocityObstacle
from pymapf.decentralized.position import Position

sim = MultiAgentVelocityObstacle(simulation_time=8.0)
sim.register_agent("r2d2", Position(0, 3), Position(10, 7))
sim.register_agent("bb8", Position(0, 7), Position(5, 10))
sim.register_agent("c3po", Position(10, 7), Position(5, 0))
sim.run_simulation()
sim.visualize("filename_test_2", 10, 10)

If you use the project in your work, please consider citing it with:

@misc{https://doi.org/10.13140/rg.2.2.14030.28486,
  doi = {10.13140/RG.2.2.14030.28486},
  url = {https://rgdoi.net/10.13140/RG.2.2.14030.28486},
  author = {Erwin Lejeune and Sampreet Sarkar},
  language = {en},
  title = {Survey of the Multi-Agent Pathfinding Solutions},
  publisher = {Unpublished},
  year = {2021}
}

List of publications & preprints using pymapf (please open a pull request to add missing entries):

• Survey of MAPF solutions (January 2021)

Open an issue to state clearly the contribution you want to make. Upon aproval send in a PR with the Issue referenced. (Implement Issue #No / Fix Issue #No).

• Erwin Lejeune
• Sampreet Sarkar