Abstract
This work demonstrates the use of genetic algorithms in optimized view planning for 3D reconstruction applications using small unmanned aerial vehicles (UAVs). The quality of UAV site models is currently highly dependent on manual pilot operations or grid-based automation solutions. When applied to 3D structures, these approaches can result in gaps in the total coverage or inconsistency in final model resolution. Genetic algorithms can effectively explore the search space to locate image positions that produce high quality models in terms of coverage and accuracy. A fitness function is defined, and optimization parameters are selected through semi-exhaustive search. A novel simulation environment for evaluating view plans is demonstrated using terrain generation software. The view planning algorithm is tested in two separate simulation cases: a water drainage structure and a reservoir levee, as representative samples of infrastructure monitoring. The optimized flight plan is compared against three alternate flight plans in each case. The optimized view plan is found to yield terrain models with up to 43% greater accuracy than a standard grid flight pattern, while maintaining comparable coverage and completeness.
Highlights
Introductionunmanned aerial vehicles (UAVs), are useful remote-sensing platforms for infrastructure monitoring and inspection
Unmanned aerial vehicles, or unmanned aerial vehicles (UAVs), are useful remote-sensing platforms for infrastructure monitoring and inspection
The current study extends and improves upon previous work by using a genetic algorithm for view planning in a large and unstructured environments common in UAV terrain modeling [44]
Summary
UAVs, are useful remote-sensing platforms for infrastructure monitoring and inspection. The small size and maneuverability of UAVs make them highly mobile sensor platforms that can quickly and gather information about an environment that would otherwise be difficult to obtain. UAVs have been used largely in military applications, new industrial opportunities may utilize UAVs as remote-sensing tools in areas as diverse as precision agriculture, landslide observation, pipeline surveillance, photogrammetric modeling and infrastructure monitoring [1,2,3,4,5,6,7]. One attractive use of UAVs for many industries is as a highly mobile sensor platform for 3D reconstruction [9]. The resulting models are useful for observation of terrain changes [11], inspection of existing infrastructure [12] and environmental monitoring [13]
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