Collaborative Control of Autonomous Unmanned Aerial Vehicles within a Changing Operation Conditions.

Research in unmanned vehicle systems has perked up noticeably in the last 20 years. These robot vehicles, which operate in the air, sea and on land have both military and civilian applications, such as reconnaissance, striking, surveillance, inspection, exploration, mapping, payload delivery, search and rescue. This growing interest worldwide is due to the efficacy of using such robots in harsh and uncertain environment as well as during the war on terror. For instance, Unmanned Aerial Vehicles are employed into many applications such surveillance, search and rescue, environment monitoring, disaster relief, delivering medicines to remote villages, forest fires, and remote inspection of nuclear sites such as inspecting Japans Fukushima Daiichi nuclear power plant. Globally, development of such mobile robots is affirming an important strategic benefit. Starting early as remote controlled vehicles, they have also experienced a considerable advance towards autonomy at all levels. Cooperation between autonomous vehicles (agents) working in teams extend these robots capabilities to a level beyond what can be achieved by a single vehicle. In addition, such cooperation has shown promising advantages in terms of robustness, adaptability, reconfigurability, flexibility, and scalability. Cooperation is defined as a close relationship among all agents in the team with information sharing playing an important role. This includes cooperative tasks like formation control and flocking, collision avoidance, rendezvous at the control level, cooperative perception at the information level, and cooperative planning and decision making at the mission level. These tasks may be performed in a central (all information collected at a single hub, which also computes action for all agents) or in distributed fashion, (actions are computed locally, without necessary access to global knowledge). These high-order nonlinear systems have been the focus of a multitude of research studies that considered a simple model of the system's dynamic and more then often a special class of the affine systems set. There is a clear lack of research that addresses the general modeling of Unmanned Vehicle (UV) in Port Controlled Hamiltonian (PCH) form. In addition to being of theoretical nature, most these studies focus on one a predetermined UV model and assume an ideal working environment ignoring the effect of changing environment on the communication and control quality in an integrated manner. For instance, a group of space shuttles moving from the atmosphere to the outer space will exchange different forces and energies with the environment. Moreover, Studies using an experimental platform to validate any of the proposed control strategies are scarce in the literature. This proposal addresses these knowledge gaps. Indeed, by extending recent research results of the PI on Unmanned Aerial Vehicles (UAV) and Autonomous Underwater Vehicles (AUV), we propose to use PCH formalism to have a general nonlinear model that represents a common modeling framework of many UVs. We take advantage of this common modeling framework to capture the effect of changing environment on the UV. We also propose to develop a fleet of heterogeneous autonomous vehicles composed of rotary wing unmanned airplanes such as quadrotors or helicopters and also ground vehicles. The objective is to study the quality of formation control and leader-follower tracking in varying working environment with characteristics that directly affect their autonomy