Approach for autonomous control of unmanned aerial vehicle using intelligent agents for knowledge creation

This paper describes the development of a planned approach for autonomous operation of an unmanned aerial vehicle (UAV). A hybrid approach seeks to provide knowledge generation through the application of artificial intelligence (AI) and intelligent agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches, which include expert systems, neural networks, intelligent agents, fuzzy logic, and complex adaptive systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many unmanned vehicles such as: rovers, ocean explorers, robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.