More and more autonomous unmanned aerial vehicle (UAV) applications require the ability to perceive environmental aspects through sensors. Typically, such onboard perceptual capabilities are highly aligned to and therefore limited to specified perceptual tasks, such as object detection or tracking, and the planned field of application, e.g. civil security or military surveillance. To counteract these limitations, we propose to adapt the installed set of perceptual functions for unexpected perceptual tasks on UAV platforms during mission. Therefore, we apply background knowledge using case-based reasoning (CBR) on already installed functions to come up with task-adapted altered capabilities improving result quality and versatility to ensure mission effectiveness.
«More and more autonomous unmanned aerial vehicle (UAV) applications require the ability to perceive environmental aspects through sensors. Typically, such onboard perceptual capabilities are highly aligned to and therefore limited to specified perceptual tasks, such as object detection or tracking, and the planned field of application, e.g. civil security or military surveillance. To counteract these limitations, we propose to adapt the installed set of perceptual functions for unexpected percep...
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