An Efficient Multi-Agent Path Finding Solver for Car-Like Robots

Continuous CBS - a modification of conflict based search algorithm, that allows to perform actions (move, wait) of arbitrary duration. Timeline is not discretized, i.e. is continuous.

This is a multi-agent path planning(also known as Multi-Agent Path Finding, MAPF) algorithm package for ROS

Iterative Refinement for Real-Time Multi-Robot Path Planning (IROS-21)

Algorithm for prioritized multi-agent path finding (MAPF) in grid-worlds. Moves into arbitrary directions are allowed (each agent is allowed to follow any-angle path on the grid). Timeline is continuous, i.e. action durations are not explicitly discretized into timesteps. Different agents' size and moving speed are supported. Planning is carried…

Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding (AIJ-22)

simple multi-agent pathfinding (MAPF) visualizer for research usage

Engineering LaCAM*: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding (AAMAS-24)

LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding (AAAI-23)

[AAAI-2024] Follower: This study addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed Follower approach utilizes a combination of a planning algorithm for constructing a long-term plan and reinforcement learning for resolving local conflicts.

Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding (IJCAI-23)

Offline Time-Independent Multi-Agent Path Planning (IJCAI-22, T-RO-23)

[AAAI-2024] MATS-LP addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed approach utilizes a combination of Monte Carlo Tree Search and reinforcement learning for resolving conflicts.

This is the repo for the team Pikachu's solution in the League of Robot Competition 2023. Our solution won the Overall Best and Fast Mover tracks and ranked second in the Line Honours track.

[AAAI-2024] Follower: This study addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed Follower approach utilizes a combination of a planning algorithm for constructing a long-term plan and reinforcement learning for resolving local conflicts.

Explainable Multi-Agent Path Finder (XMAPF, work in progress) based on Lazy Conflict-Based Search (Gange, Harabor and Stuckey, 2021).

A caching approach in the warehouse based on the LACAM algorithm in Lifelong Muli-Agent Path Finding

This software solves the capacitated multi agent pickup and delivery problem using OR-Tools from Google.

Implementation of some pathfinding and multi-agent pathfinding algorithms

[AAAI-2024] MATS-LP addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed approach utilizes a combination of Monte Carlo Tree Search and reinforcement learning for resolving conflicts.