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arxiv: 1901.05506 · v3 · pith:MN2ER5GYnew · submitted 2019-01-16 · 💻 cs.AI

Multi-Agent Pathfinding with Continuous Time

classification 💻 cs.AI
keywords algorithmagentsmapfmulti-agentpathfindingtimecontinuousplanning
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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 was on grids, assumed agents' actions have uniform duration, and that time is discretized into timesteps. We propose a MAPF algorithm that does not rely on these assumptions, is complete, and provides provably optimal solutions. This algorithm is based on a novel adaptation of Safe interval path planning (SIPP), a continuous time single-agent planning algorithm, and a modified version of Conflict-based search (CBS), a state of the art multi-agent pathfinding algorithm. We analyze this algorithm, discuss its pros and cons, and evaluate it experimentally on several standard benchmarks.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. On the Tour Towards DPLL(MAPF) and Beyond

    cs.AI 2019-07 unverdicted novelty 2.0

    Discusses the research steps needed to create a fully integrated DPLL(MAPF) solver for optimal multi-agent path finding via SMT, contrasting it with current loose integrations.