Research/ MULTI-ROBOT SYSTEMS
RF-Modulated Adaptive Communication Improves Multi-Agent Robotic Exploration
Lorin Achey, Breanne Crockett, Christoffer Heckman, Bradley Hayes
Multi-Robot & SwarmsOpenAlex topic: Modular Robots and Swarm Intelligence · Surface Mobility & TerramechanicsOpenAlex keyword: cave environment · Motion Planning & NavigationOpenAlex topic: Robotic Path Planning Algorithms
arXivcs.ROOpenAlexRobotic Path Planning Algorithms · Modular Robots and Swarm Intelligence · Distributed Control Multi-Agent Systems
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.