Abstract
Abstract. In recent years, the proliferation and further development of unmanned aerial vehicles (UAVs) led to a great number of key technologies, advances and opportunities especially in the realm of time-critical applications. UAVs as a platform provide a unique combination of flexibility, affordability and sensor technology which enables the design of cost-effective and intriguing services particularly for disaster response. This contribution presents a concept for UAV-based near real-time mapping system for disaster relief to provide decision-making support for first responders particularly for possible disaster scenarios in Austria. We outline our system concept and its respective architecture, discuss requirements from a stakeholder perspective as well as legal regulations and initiatives at an EU level. In the methodology section of this paper, the preliminary data processing pipeline with respect to the near real-time orthomosaic generation and the semantic segmentation network are presented. Lastly, first experimental results of the pipeline are shown, and further advances are discussed.
Highlights
unmanned aerial vehicles (UAVs) have proven to be an important instrument for various disaster scenarios (Alamouri et al, 2019; Erdelj et al, 2017)
Since the orthomosaic generation is not fully optimised yet and the images were not resampled before processing, the procedure had to be locked at two frames per second
Most of the steps in the orthomosaic generation process potentially allow for buffering and caching the data and do not require absolute real-time computation, feature tracking during the visual SLAM pipeline is prone to interruption using higher framerates
Summary
UAVs have proven to be an important instrument for various disaster scenarios (Alamouri et al, 2019; Erdelj et al, 2017). Requirements and limitations on image orientation accuracy, image resolution as well as processing performance let alone the derivation of tertiary products such as semantic labels need to be well balanced for such application-driven developments. To this end, we design the system with the intention to share the processing load between an air and a ground segment. For additional information on the situation, further processing is conducted successively and in parallel on the ground station. These processes are usually computationally expensive and are performed on the ground station
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