When Semantics Connect the Swarm: LLM-Driven Fuzzy Control for Cooperative Multi-Robot Underwater Coverage

TL;DR

This paper introduces a semantics-guided fuzzy control framework that leverages Large Language Models to enable cooperative multi-robot underwater coverage in GPS-denied, uncertain environments, improving navigation and coordination.

Contribution

It presents a novel integration of LLMs with fuzzy control and semantic communication for robust underwater multi-robot cooperation without global localization.

Findings

Achieves reliable obstacle avoidance and exploration in reef-like environments.

Enhances cooperative coverage efficiency under limited sensing and communication.

Demonstrates robustness and adaptability in simulated underwater scenarios.

Abstract

Underwater multi-robot cooperative coverage remains challenging due to partial observability, limited communication, environmental uncertainty, and the lack of access to global localization. To address these issues, this paper presents a semantics-guided fuzzy control framework that couples Large Language Models (LLMs) with interpretable control and lightweight coordination. Raw multimodal observations are compressed by the LLM into compact, human-interpretable semantic tokens that summarize obstacles, unexplored regions, and Objects Of Interest (OOIs) under uncertain perception. A fuzzy inference system with pre-defined membership functions then maps these tokens into smooth and stable steering and gait commands, enabling reliable navigation without relying on global positioning. Then, we further coordinate multiple robots by introducing semantic communication that shares intent and local context in linguistic form, enabling agreement on who explores where while avoiding redundant revisits. Extensive simulations in unknown reef-like environments show that, under limited sensing and communication, the proposed framework achieves robust OOI-oriented navigation and cooperative coverage with improved efficiency and adaptability, narrowing the gap between semantic cognition and distributed underwater control in GPS-denied, map-free conditions.