Resource aware and incremental mosaics of wide areas from small-scale UAVs

Abstract

Small-scale unmanned aerial vehicles (UAVs) are an emerging research area and have been recently demonstrated in many applications including disaster response management, construction site monitoring and wide area surveillance where multiple UAVs impose various benefits. In this work we present a system composed of multiple networked UAVs for autonomously monitoring a wide area scenario. Each UAV is able to follow waypoints and capture high-resolution images. In order to overcome the strong resource limitations we implement an incremental approach for generating an orthographic mosaic from the individual images. Captured images are pre-processed on-board, annotated with other sensor data and transferred by a prioritized transmission scheme. The ultimate goal of our approach is to generate an overview mosaic as fast as possible and to improve its quality over time. The mosaicking exploits position and orientation data of the UAV to compute rough image projections which are incrementally refined by scene structure analysis when more image data is available. We evaluate our incremental mosaicking in the strongly resource limited UAV network composed of up to three concurrently flying UAVs. Our results are compared to state-of-the-art mosaicking methods and show a unique performance in our dedicated application scenarios.