RF-Modulated Adaptive Communication Improves Multi-Agent Robotic Exploration

2026-02-12

AI Summary

This work addresses the challenge of inefficient exploration in multi-robot systems operating under communication constraints, where poor coordination and unreliable links often degrade performance. The authors propose the Adaptive RF Transmission (ART) algorithm, which uniquely integrates data payload awareness with real-time RF signal strength to dynamically adjust communication positions, thereby avoiding unproductive backtracking. To ensure high-fidelity data exchange, the ART-SST mechanism is introduced. By jointly optimizing communication behavior and exploration trajectories through communication-aware planning, dynamic RF modulation, and heterogeneous multi-robot collaboration, the approach overcomes the limitations of conventional fixed-strategy methods. Extensive evaluations across more than 480 cave simulations demonstrate that, compared to baseline approaches, the proposed method reduces exploration distance by up to 58% and shortens task completion time by as much as 52%.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

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.

Problem

• multi-agent robotic exploration
• communication-constrained environments
• reliable coordination
• efficient communication

Innovation

• Adaptive-RF Transmission
• multi-agent robotic exploration
• communication-aware planning
• signal strength threshold
• payload-aware communication