Chao Qu

TL;DR: A fruit counting pipeline based on deep learning that accurately counts fruit in unstructured environments and is able to perform well even on highly occluded fruits that are challenging for human labelers to annotate is described.

TL;DR: The design and development of a light-weight, multi-spectral 3D imaging device that can be used for automated monitoring in precision agriculture, and techniques to extract four key data products - plant morphology, canopy volume, leaf area index, and fruit counts - are described.

TL;DR: The system design and software architecture of the proposed solution are described and how all the distinct components can be integrated to enable smooth robot operation are showcased.

TL;DR: In this article, an end-to-end pipeline for tree diameter estimation based on semantic segmentation and lidar odometry and mapping is described, which is more robust, scalable, and automatically generates tree diameter estimations.

TL;DR: In this paper, a system design and software architecture for a flying robot to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment is presented.