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This paper introduces Adaptive-RF Transmission (ART), a communication-aware planning algorithm for multi-agent robotic exploration that modulates transmission location based on signal strength and data payload size. ART aims to improve coordination and efficiency in communication-limited environments by enabling heterogeneous robot teams to share information without excessive backtracking. Simulation results across cave-inspired environments show that ART and its extension, ART-SST, outperform existing strategies, achieving significant reductions in distance traveled and exploration time.
Robots can explore complex, communication-constrained environments up to 52% faster by dynamically modulating their transmission locations based on signal strength and data payload size.
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.