Paper Title
Hybrid Pigeon Inspired Optimization (h-PIO) Algorithm for UAV Swarm

Abstract
Autonomy of unmanned aerial systems depends on self reliance, de-centralized decision making capabilities of Unmanned Aerial Vehicle (UAV) entities. Autonomy hinges on Co-ordination & control of Multi Agent aerial System. Route planning using modified Ant Colony Optimization (m-ACO) is the initial step in developing autonomous Aerial systems. Avian Navigation & Asset Tracking is discussed in this paper employing bio – inspired Pigeon Optimization Algorithm (h-PIO). The research paper proposes Markov Decision process (MDP) based Collision Avoidance System (CAS) Algorithm. Co-operative maneuvering using Swarm Co-ordination & Control is achieved employing rigid cohesive systems with loose coupling. Flying Adhoc Network (FANET) serves as the backbone communication using 802.11 b/n/g for the UAV Swarm. Keywords - Pigeon Inspired Optimization Algorithm, UAV, Swarm, Formation Control, Co-ordination