Python implementation of a bunch of multi-robot path-planning algorithms.
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Updated
Apr 5, 2023 - Python
Python implementation of a bunch of multi-robot path-planning algorithms.
Anonymous Multi-Agent Path Finding (MAPF) with Conflict-Based Search and Space-Time A*
Iterative Refinement for Real-Time Multi-Robot Path Planning (IROS-21)
BCP-MAPF – branch-and-cut-and-price for multi-agent path finding
Multi-agent pathfinding via Conflict Based Search
Conflict-based search for multi-agent path finding (MAPF)
simple multi-agent pathfinding (MAPF) visualizer for research usage
Engineering LaCAM*: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding (AAMAS-24)
Implementations of various algorithms used to solve the problem of Multi-Agent Pickup and Delivery (a generalization of Multi-Agent Path Finding).
Solution of NeurIPS 2020 Flatland Challenge from the team An_old_driver.
A solution of Multi-Agent Path Finding problem
LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding (AAAI-23)
Based on David Silver's paper "Cooperative Pathfinding"
Minimal Python implementation of PIBT for MAPF
Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding (IJCAI-23)
Mixed Strategy Nash Equilibrium for Crowd Navigation (IJRR)
Minimal Python implementation of LaCAM* for MAPF
The Ranking Cost algorithm for multi-path routing of gridworld.(多智能体路径规划,电路规划)
The purpose of this simulator is simulates and allows visualization of the evacuation process of people located in buildings during emergencies.
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