Memetic technique for multiple unmanned aerial vehicles.
Doan Van Khanh.
Date of Issue2011
School of Electrical and Electronic Engineering
This thesis focuses on a memetic computation approach for area coverage involving multiple unmanned aerial vehicles (UAVs). In some real–life scenarios, such as a battlefield or an earthquake disaster area, access using manned vehicles may present severe challenges for practical reasons. In scanning a region, each UAV will typically follow a certain pattern of combing through a region. To our knowledge, there has been no attempt to quantitatively model the turning time cost for UAV scanning. Such quantitative modeling allows for reliable estimation of the scanning time for the different scanning strategies. We describe the formulation of a turning time model for estimating the time cost for UAVs changing direction during flight. Based on this model, we explore two strategies of scanning as a basis for a memetic computing search; the raster and circular scanning strategies. For raster scanning, the UAV flies in parallel to one edge of a polygon while for circular scanning, the UAV flies in cyclical path defined by the boundary starting from the outer to the inner region or vice versa. The objective of the memetic approach is to minimize scanning time through polygon decomposition as a form of tasks division between UAVs and for each sub-polygon, a pattern of scanning is specified such that the overall turning time is reduced accordingly. Validation through flight tests conducted at Boeing’s Vehicles Swarm Technology Laboratory (VSTL) showed performance consistent with the estimation model in the algorithm.
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation