SwarnRaft: Leveraging Consensus for Robust Drone Swarm Coordination in GNSS-Degraded Environments

2025-08-01

AI Summary

To address UAV swarm navigation failure, loss of coordination, and mission disruption caused by GNSS signal degradation—due to interference, occlusion, or adversarial attacks—this paper proposes a decentralized, consensus-driven robust cooperative navigation method. The approach innovatively integrates a lightweight Raft consensus algorithm into a multi-vehicle distributed architecture, synergistically fusing GNSS, onboard inertial and visual sensors, and WiFi-based peer-to-peer communication. In GNSS-denied environments, it enables cross-node collaborative validation of position and heading states, along with real-time identification and reconfiguration of anomalous nodes. Crucially, it eliminates reliance on centralized infrastructure, thereby ensuring state consistency and continuous navigation integrity. Experimental results demonstrate that the system maintains stable swarm coordination under partial node disconnection or complete GNSS outages, exhibiting strong fault tolerance, resilience to interference, high scalability, and practical deployability in real-world operational scenarios.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Coordination and Collaboration

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Responsible Web: Consent frameworks and practices on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Unmanned aerial vehicle (UAV) swarms are increasingly used in critical applications such as aerial mapping, environmental monitoring, and autonomous delivery. However, the reliability of these systems is highly dependent on uninterrupted access to the Global Navigation Satellite Systems (GNSS) signals, which can be disrupted in real-world scenarios due to interference, environmental conditions, or adversarial attacks, causing disorientation, collision risks, and mission failure. This paper proposes SwarnRaft, a blockchain-inspired positioning and consensus framework for maintaining coordination and data integrity in UAV swarms operating under GNSS-denied conditions. SwarnRaft leverages the Raft consensus algorithm to enable distributed drones (nodes) to agree on state updates such as location and heading, even in the absence of GNSS signals for one or more nodes. In our prototype, each node uses GNSS and local sensing, and communicates over WiFi in a simulated swarm. Upon signal loss, consensus is used to reconstruct or verify the position of the failed node based on its last known state and trajectory. Our system demonstrates robustness in maintaining swarm coherence and fault tolerance through a lightweight, scalable communication model. This work offers a practical and secure foundation for decentralized drone operation in unpredictable environments.

Problem

• Maintain drone swarm coordination without GNSS signals
• Ensure data integrity in GNSS-degraded environments
• Provide fault tolerance for UAVs in unpredictable conditions

Innovation

• Blockchain-inspired consensus for drone coordination
• Raft algorithm for state agreement without GNSS
• Lightweight WiFi communication for swarm coherence