In this paper, a method for accurate path following for miniature air vehicles is developed. The method is based on the notion of vector fields, which are used to generate desired course inputs to inner-loop attitude control laws. Vector field path following control laws are developed for straight-line paths and circular arcs and orbits. Lyapunov stability arguments are used to demonstrate asymptotic decay of path following errors in the presence of constant wind disturbances. Experimental flight tests have demonstrated mean path following errors on less than one wingspan for straight-line and orbit paths, and less than three wingspans for paths with frequent changes in direction.

The objective of this paper is to explore the feasibility of using multiple low-altitude, short endurance (LASE) unmanned air vehicles (UAVs) to cooperatively monitor and track the propagation of large forest fires. A real-time algorithm for tracking the perimeter of a fire with an on-board infrared sensor is developed. Using this algorithm, we develop a decentralized multiple-UAV approach to monitoring the perimeter of the fire. The UAVs are assumed to have limited communication and sensing range. The effectiveness of the approach is demonstrated in simulation using a 6 DOF dynamic model for the UAV and numerical propagation model for the forest fire. Salient features of the approach include the ability to monitor a changing fire perimeter, the ability to systematically add and remove UAVs from the team, and the ability to supply time-critical information to forest fire fighters.

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Numerous applications require aerial surveillance. Civilian applications include monitoring forest fires, oil fields and pipelines, and tracking wildlife. Applications to homeland security include border patrol and monitoring the perimeter of nuclear power plants. Military applications are numerous. The current approach to these applications is to use a single manned vehicle for surveillance. However, manned vehicles are typically large and expensive. In addition, hazardous environments and operator fatigue can potentially threaten the life of the pilot. Therefore, there is a critical need for automating aerial surveillance using unmanned air vehicles (UAVs). This paper gives an overview of a cooperative control strategy for aerial surveillance that has been successfully flight tested on small (48 inch wingspan) UAVs. Our approach to cooperative control problems can be summarized in four steps: (1) the definition of a cooperation constraint and cooperation objective; (2) the definition of a coordination variable as the minimal amount of information needed to effect cooperation; (3) the design of a centralized cooperation strategy; and (4) the use of consensus schemes to transform the centralized strategy into a decentralized algorithm. The effectiveness of the solution will be shown using both high fidelity simulation and actual flight tests.

This paper presents an end-to-end solution to the battlefield scenario where M unmanned air vehicles are assigned to strike N known targets, in the presence of dynamic threats. The problem is decomposed into the subproblems of (1) cooperative target assignment, (2) coordinated UAV intercept, (3) path planning, and (4) feasible trajectory generation. The design technique is based on a hierarchical approach t o coordinated control. Detailed simulation results are presented.

This paper presents an end-to-end solution to the cooperative control problem represented by the scenario where unmanned air vehicles (UAVs) are assigned to transition through known target locations in the presence of dynamic threats. The problem is decomposed into the subproblems of: 1) cooperative target assignment; 2) coordinated UAV intercept; 3) path planning; 4) feasible trajectory generation; and 5) asymptotic trajectory following. The design technique is based on a hierarchical approach to coordinated control. Simulation results are presented to demonstrate the effectiveness of the approach.

Frequent and detailed updates of the development of a forest fire are essential for effective and safe fire fighting. Since a forest fire is typically inaccessible by ground vehicles due to mountainous terrain, small Unmanned Air Vehicles (UAVs) are emerging as a promising solution to the problem of monitoring large forest fires. In this paper we present an effective path planning algorithm for a UAV utilizing infrared images that are collected on-board in realtime. In order to demonstrate the effectiveness of our path planning algorithm in realistic scenarios, we implemented the forest fire propagation model EMBYR to simulate the time evolution of a typical forest fire. We also introduce a new cooperative control mission concept where multiple Low-Altitude, Short-Endurance (LASE) UAVs are used for fire monitoring. By simultaneously deploying multiple UAVs, the effectiveness of the mission in terms of information update rate can be improved dramatically.