Multi-Agent Path Finding: Conflict-Based Search
Multi-Agent Path Finding: Conflict-Based Search
Implemented an efficient Conflict-Based Search (CBS) algorithm for Multi-Agent Path Finding, with an OpenCV-based animation system to visualize agent movements and path planning in grid-based environments.
Real-time visualization of the CBS algorithm solving multi-agent pathfinding conflicts
Project Overview
In the multi-agent path finding problem (MAPF), paths should be found for several agents, each with a different start and goal position such that agents do not collide. This implementation provides a complete solution using the CBS algorithm with real-time visualization.
Algorithm Implementation
Conflict-Based Search (CBS)
CBS is a two-level algorithm that provides optimal solutions:
- High Level: Search performed on a tree based on conflicts between agents
- Low Level: Search performed for a single agent at a time
- Advantage: Examines fewer states than A* while maintaining optimality
Demo Video
Watch the algorithm in action:
Research Background
This implementation is based on the seminal paper:
Conflict Based Search (CBS) - Sharon, G., Stern, R., Felner, A., & Sturtevant, N. R. (2015). “Conflict-based search for optimal multi-agent pathfinding.” Artificial Intelligence, 219, 40-66.
Performance Results
- Optimality: Guaranteed optimal solutions
- Efficiency: Significant speedup over global A*-based approaches
- Scalability: Tested with multiple agents in various grid configurations
- Real-time Visualization: Smooth animation at 30+ FPS
Technologies Used
- Python: Core implementation language
- OpenCV: Visualization and animation
- NumPy: Numerical computations
- Matplotlib: Additional plotting capabilities
- Algorithm Design: A*, CBS, conflict detection
Repository
Explore the complete implementation with detailed documentation:
Credit: RAP-Lab from SJTU for research guidance and algorithmic insights.
Applications
This MAPF solution has applications in:
- Warehouse Robotics: Multiple robots navigating shared spaces
- Autonomous Vehicles: Coordinated vehicle routing
- Game AI: Strategic unit movement in real-time strategy games
- Drone Swarms: Coordinated multi-drone operations