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arXiv · 2608.11895

Scalable Multi-Agent Maze Traversal with Local Communication

Julian Rau·Jahir Argote-Gerald·Grace McFassel·Genki Miyauchi·Paul Trodden·Roderich Groß
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Abstract

Cave networks, pipe systems, and similar maze-like environments pose significant challenges for multi-agent navigation in unknown settings with limited communication. We propose a distributed algorithm that enables agents to collectively traverse an unknown, possibly cyclic graph. Agents enter sequentially at a designated start node and are tasked to localize and reach an undisclosed goal while avoiding collisions. They coordinate via local communication using leader-follower relationships and leader switching. At any moment in time, exploration is performed by only one of the agents, which runs a single-agent maze solver. We prove that the algorithm is complete, that its makespan is asymptotically equivalent (in the number of agents) to that of an optimal full-knowledge strategy, and derive its time and space complexity. Simulations with up to $625$ agents show a decreasing average sum-of-fuels as the number of agents increases and demonstrate that the proposed approach outperforms a na\"ive baseline in which all agents independently execute the single-agent solver.

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Julian Rau, Jahir Argote-Gerald, Grace McFassel, Genki Miyauchi, Paul Trodden, Roderich Groß. 2026-08-12. Scalable Multi-Agent Maze Traversal with Local Communication. https://arxiv.org/abs/2608.11895

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