Swarm Robotics Algorithms for Disaster Relief Communication Networks

Abstract

Disaster relief operations often face severe challenges in establishing reliable communication networks due to damaged infrastructure and harsh environments. Swarm robotics, inspired by the collective behavior of social insects, offers a promising solution by deploying multiple autonomous robots that cooperate to create resilient, selforganizing communication networks in disaster-affected areas. This study investigates swarm robotics algorithms tailored to optimize disaster relief communication networks by enhancing coverage, connectivity, and fault tolerance. The paper focuses on decentralized algorithms enabling robotic swarms to autonomously position themselves to maintain network connectivity while adapting to dynamic conditions such as obstacles, node failures, and changing mission priorities. The algorithms utilize bio-inspired behaviors such as flocking, foraging, and collective decisionmaking to coordinate swarm movements and communication relay formations. A systematic literature review was conducted on swarm algorithms applied in wireless sensor networks, mobile ad-hoc networks, and robotic deployments in disaster scenarios up to 2019. The research methodology involved simulationbased evaluations of key algorithms including Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and behavior-based control approaches. Metrics such as network coverage, data throughput, latency, and energy efficiency were analyzed. Key findings reveal that hybrid swarm algorithms combining heuristic optimization and local interaction rules outperform purely centralized or random deployment strategies. The swarm exhibits robust adaptability to node loss and environmental changes, maintaining network integrity with minimal human intervention. Challenges such as communication overhead, scalability, and real-time responsiveness are discussed. The workflow proposed integrates environment sensing, adaptive movement control, communication relay establishment, and fault recovery. Advantages include rapid deployment, scalability, and fault tolerance, while disadvantages involve computational complexity and energy constraints of individual robots. The study concludes that swarm robotics algorithms offer significant potential to revolutionize disaster relief communication by providing flexible, scalable, and resilient networks. Future work should explore hardware implementation, energy-aware strategies, and integration with existing emergency communication infrastructure.