RF-Modulated Adaptive Communication Improves Multi-Agent Robotic Exploration

TL;DR

This paper presents a novel adaptive communication planning algorithm for multi-agent robotic exploration that dynamically modulates transmission based on signal strength and payload, significantly improving efficiency and speed.

Contribution

Introduction of ART, a dynamic, communication-aware planning algorithm, and its extension ART-SST, for improved multi-agent exploration in communication-limited environments.

Findings

Up to 58% reduction in distance traveled.

Up to 52% faster exploration times.

Consistent outperformance of existing strategies.

Abstract

Reliable coordination and efficient communication are critical challenges for multi-agent robotic exploration of environments where communication is limited. This work introduces Adaptive-RF Transmission (ART), a novel communication-aware planning algorithm that dynamically modulates transmission location based on signal strength and data payload size, enabling heterogeneous robot teams to share information efficiently without unnecessary backtracking. We further explore an extension to this approach called ART-SST, which enforces signal strength thresholds for high-fidelity data delivery. Through over 480 simulations across three cave-inspired environments, ART consistently outperforms existing strategies, including full rendezvous and minimum-signal heuristic approaches, achieving up to a 58% reduction in distance traveled and up to 52% faster exploration times compared to baseline methods. These results demonstrate that adaptive, payload-aware communication significantly improves coverage efficiency and mission speed in complex, communication-constrained environments, offering a promising foundation for future planetary exploration and search-and-rescue missions.