Swarm Eye: A Distributed Autonomous Surveillance System - Khan, Faisal (Cranfield University, 2011)
Having precise information in complex, dynamic, highly demanding and stressful situations is of utmost importance for quick, objective and well informed decision making. Knowing the exact position of a unit in complex, unknown or confusing environment such as ragged mountain areas or narrow labyrinthine alleys of a city can be very challenging and is of high relevance in tactical decision making. Conventional means such as GPS and satellite photos are important information sources but provide only limited and static information. In tactical situations rich 3D images and dynamically self‐adapting information are needed to overcome this restriction; this information should be collected where it is available. Distributed ground teams or swarms of UAVs can provide different and dynamic views of a tactical scene. Swarms are sets of interconnected units that can be arranged and coordinated in any flexible way to execute a specific task in a distributed manner. The Swarm Eye is a concept that provides a platform for combining the powerful techniques of swarm intelligence, emergent behaviour and computer graphics in one system. Swarm Eye allows the testing of new image processing concepts for a better and well informed decision making process. By using advanced collaboratively acting eye units, the system can observe, gather and process images in parallel to provide high value information. To capture visual data from an autonomous airborne unit, the unit has to be in the right position in order to get the best visual sight. This Swarm Eye system also provides autonomous formations for UAV or airborne units to form a better formation autonomously in distributed manner in accordance with the situation.