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.

翻译：在通信受限环境中，可靠协同与高效通信是多智能体机器人探索面临的关键挑战。本研究提出自适应射频传输算法（ART），这是一种新型的通信感知规划算法，可根据信号强度与数据负载大小动态调制传输位置，使异构机器人团队无需冗余折返即可高效共享信息。我们进一步提出该方法的扩展版本ART-SST，通过强制执行信号强度阈值来保障高保真度数据传输。在三种洞穴模拟环境中进行的480余次仿真实验表明，ART算法在行进距离上较基准方法最多减少58%，探索时间最多加快52%，其性能持续优于包括完全交会策略与最小信号启发式方法在内的现有策略。这些结果证明，在复杂通信受限环境中，具备负载感知能力的自适应通信能显著提升覆盖效率与任务执行速度，为未来行星探索与搜救任务提供了可靠的技术基础。