| Abstrakt: |
In recent years, owing to the advance in image processing using deep learning, autonomous unmanned aerial vehicle (UAV) navigation based on image recognition has become possible. However, several image-based deep learning methods focus primarily on single-task autonomous UAV systems, which cannot perform other required tasks. Meanwhile, deep learning methods based on multi-task learning, which are suitable for multi-tasking autonomous UAV systems, have not been sufficiently researched. Therefore, in this study, we propose a UAV flight control method that can enable correction of a UAV's self-position, self-direction, and recognition/selection of multiple movement directions using multi-task learning for exploring an unknown indoor environment, which is based only on information from monocular camera images. |
