Abstract
Ecology monitoring of large areas of farmland, rangelands and wilderness relies on routine map building and picture compilation, traditionally performed using high-flying surveys with manned-aircraft or through satellite remote sensing. Unmanned Aerial Vehicles (UAVs) are a promising alternative as a data collection platform due to the small-size, longer endurance and thus cost-effectiveness of these systems. Additionally UAVs can fly lower to the ground, collecting higher-resolution imagery than with manned aircraft or satellites. This paper discusses the development and experimental evaluation of systems and algorithms for airborne environment mapping, object detection and vegetation classification using low-cost sensor data including monocular vision collected from a UAV. Experimental results of the system are presented in multiple flights of our UAV system in three different environments and two different ecology monitoring applications, operating in remote locations in outback Australia.
This work is supported by Meat and Livestock Australia (MLA) under project code B.NBP.0474, “UAV Surveillance Systems for the Management of Woody Weeds”, the Australian Weeds Research Council (AWRC) under project code AWRC08-04, “Using UAVs and Innovative Classification Algorithms in the Detection of Cacti” and the ARC Centre of Excellence programme, funded by the Australian Research Council (ARC) and the New South Wales State Government.
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Bryson, M., Reid, A., Hung, C., Ramos, F.T., Sukkarieh, S. (2014). Cost-Effective Mapping Using Unmanned Aerial Vehicles in Ecology Monitoring Applications. In: Khatib, O., Kumar, V., Sukhatme, G. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28572-1_35
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