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EARS-Info: Information-Aware Event-Driven Reallocation for Multi-Robot Exploration

Kabeh Mohsenzadegan, Vahid Tavakkoli, Kyandoghere Kyamakya

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First announced by arXiv: 2026-10-30 · Indexed by Pub-AI: 2026-10-30 UTC

preprint

EARS-Info: Information-Aware Event-Driven Reallocation for Multi-Robot Exploration

Kabeh Mohsenzadegan, Vahid Tavakkoli, Kyandoghere Kyamakya

First announced by arXiv: 2026-10-30 · Original record ↗

arxiv
2610.38040
Explicit source versions (1)
  • v1 · Date not supplied
  1. Preprint available

    Source date: 2026-10-30 · First detected: 2026-10-30 UTC · Historical baseline

    Source evidence (1)
    • Official evidence ↗ · RSS guid=oai:arXiv.org:2610.38040v1; arxiv:announce_type=new; item pubDate (official metadata)
Abstract · arxiv

We introduce EARS-Info, an information-aware extension of Event-Driven Ant Reallocation Search for multi-robot exploration on OpenStreetMap-derived grids. It combines marginal sensing gain, feasible relocation, return-aware routing, sensing reservations, and cached shortest paths. Across 168,000 episodes comparing 30 implementations on eight city maps, EARS-Info achieves the highest mean operational score in every evaluation panel. With eight robots and 3% communication dropout, it improves the score over EARS-Safe by 5.43%, increases weighted discovery from 88.88% to 98.46%, and reduces mean energy use by 2.62%. Score differences are positive in all eight cities ($p=0.0078125$; descriptive 95% city-bootstrap interval $[0.0159,0.0694]$), with no simulated incidents across 5,600 EARS-Info episodes. These results support the complete controller; individual component advantages remain uncertain. Generalization is limited by reused geography, one training replicate, coarse maps, and adapted comparison methods.

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