ほ場内高精度マップを用いた画像範囲の限定によるインスタンスセグメンテーションの速度向上手法

抄録

In order to make precision agriculture more accurate, real-time operations for individual crops is a challenge. It is essential to measure the crop area accurately when approaching individual crops. However, existing instance segmentation methods are computationally expensive, and it is difficult to recognize crops on devices in real-time. In this paper, we develop a crop recognition method for a gripper weeding machine. By creating a high-precision crop map in advance and limiting the image area based on the map, the location and the azimuth of the vehicle from GPS units, we succeeded in the real-time and high-accurate individual crop recognition on Jetson AGX Xavier.