3 accepted papers
Object detection and semantic segmentation are two of the most widely adopted deep learning algorithms in agricultural applications. One of the major sources of variability in image quality acquired outdoors for such tasks is changing lighting conditions that can alter the appearance of the objects…
We outline a neural network-based pipeline for perception, control and planning of a 7 DoF robot for tasks that involve reaching into a dormant grapevine canopy. The proposed system consists of a 6 DoF industrial robot arm and a linear slider that can actuate on an entire grape vine. Our approach us…
The need for fast and precise measurements of plant attributes makes robotic solutions an ideal replacement for labor-intensive phenotyping processes. In this work we present a deep learning-based high throughput, online pipeline for in-situ sorghum stalk detection and grasping. We use a variation o…