Multi-Agent Pathfinding with Continuous Time

Author:

Andreychuk Anton12,Yakovlev Konstantin13,Atzmon Dor4,Stern Roni4

Affiliation:

1. Federal Research Center "Computer Science and Control" of Russian Academy of Sciences

2. Peoples’ Friendship University of Russia (RUDN University)

3. National Research University "Higher School of Economics"

4. Ben Gurion University of the Negev

Abstract

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. Most prior work on MAPF were on grids, assumed agents' actions have uniform duration, and that time is discretized into timesteps. In this work, we propose a MAPF algorithm that do not assume any of these assumptions, is complete, and provides provably optimal solutions. This algorithm is based on a novel combination of Safe Interval Path Planning (SIPP), a continuous time single agent planning algorithms, and Conflict-Based Search (CBS). We analyze this algorithm, discuss its pros and cons, and evaluate it experimentally on several standard benchmarks.

Publisher

International Joint Conferences on Artificial Intelligence Organization

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1. Receding Horizon Re-Ordering of Multi-Agent Execution Schedules;IEEE Transactions on Robotics;2024

2. Heuristics and Rescheduling in Prioritised Multi-Robot Path Planning: A Literature Review;Machines;2023-11-20

3. Non-Refined Abstractions in Counterexample Guided Abstraction Refinement for Multi-Agent Path Finding;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06

4. Counterexample Guided Abstraction Refinement with Non-Refined Abstractions for Multi-Goal Multi-Robot Path Planning;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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