Coordination of Autonomous Unmanned Air Vehicles
Researchers are developing mathematical algorithms for autonomous unmanned air vehicle cooperative control.
Future autonomous unmanned air vehicles (UAV) will need to work in teams to share information and coordinate activities in much the same way as current manned air systems. Funded by AFRL, Professor Hugh Durrant-Whyte and his research staff (see Figure 1) at the Australian Research Council's Center of Excellence for Autonomous Systems have been developing mathematical models and simulation studies to understand—and ultimately provide— this future UAV capability.
The team's research focuses on coordination and cooperation for teams of autonomous UAVs engaged in information gathering and data fusion tasks, including cooperative tracking, ground picture compilation, area exploration, and target search. The underlying mathematical model for coordination and cooperation employs quantitative probabilistic and information-theoretic models of platform and sensor abilities. This information-theoretic approach builds on established principles for distributed data fusion in sensor networks, extending these ideas to problems in the distributed control of sensing resources. The researchers have made substantial progress towards formulating, solving, and demonstrating these methods for multi-UAV systems. In particular, they have developed distributed algorithms that enable UAV team-based search and exploration operations. These search and exploration algorithms can incorporate realistic constraints on platforms and sensors—a priori constraints from the environment and weak information from external sources. To date, Prof Durrant-Whyte's research team has successfully demonstrated these algorithms on a flight simulator of midlevel fidelity (see Figure 2).
Recently, the team presented its findings to AFRL researchers at Wright- Patterson Air Force Base (AFB), Ohio, and Eglin AFB, Florida. Based on the promising results of this research effort, AFRL is funding two additional projects to further explore the mathematical aspects of the technology and facilitate real-world application through demonstrations. The first round of demonstrations will involve high-fidelity, hardware-in-the-loop simulations, culminating in a large-scale demonstration involving a UAV fleet operated by the University of Sydney (see Figure 3). AFRL's two research projects will provide significant scientific and technical advancement in the cooperative control of autonomous systems.
The availability of autonomous UAV teams capable of complex cooperative behavior will enable warfighters to execute highly complex missions effectively and safely removed from harms way (i.e., remotely). In addition to providing these advantages, the UAV technology's imaging and atmospheric sampling capabilities have the potential to support both homeland security emergency scenarios and real-time forest fire monitoring tasks.
Dr. Tae-Woo Park, of the Air Force Research Laboratory's Air Force Office of Scientific Research, and Prof Hugh Durrant-Whyte, of the University of Sydney (Australian Research Council Federation Fellow), wrote this article. For more information, contact TECH CONNECT at (800) 203-6451 or place a request at http://www.afrl.af.mil/techconn/index.htm . Reference document OSR-H-05-06.