PSO-Based Drone Swarm Coordination

Organizations deploying multiple drones for area coverage, search and rescue, or surveillance missions faced significant coordination challenges. Centralized control approaches created single points of failure and communication bottlenecks that limited scalability and resilience.

The core challenge was developing coordination algorithms that enable swarms of drones to autonomously distribute themselves across search areas, avoid collisions, adapt to dynamic obstacles, and converge on targets — all without requiring continuous communication with a central controller.

Without effective swarm coordination, multi-drone operations remained limited to manual control of small fleets, drastically reducing coverage area and mission effectiveness.

The engagement adapted particle swarm optimization (PSO) principles to multi-drone coordination, creating algorithms that enable emergent swarm behavior from simple local rules.

The engagement delivered validated PSO-based coordination algorithms demonstrated in simulation across multiple mission types. The algorithms enable drone swarms to autonomously distribute for area coverage, converge on targets, and navigate around obstacles without centralized control.

The decentralized approach ensures graceful degradation when individual drones are lost or communications are disrupted, maintaining mission effectiveness in contested environments.