Selective Chrysanthemum Harvesting Robot

Selective chrysanthemum harvesting robots aim to automate the picking process, addressing labor shortages and improving efficiency in agriculture. Current research focuses on developing robust computer vision systems, often employing deep learning architectures like YOLO and Mask R-CNN, to accurately detect and locate chrysanthemums in complex field environments, and on designing effective robotic end-effectors capable of gentle yet firm grasping and harvesting. These advancements hold significant potential for increasing agricultural productivity and reducing the reliance on manual labor, particularly for delicate crops like chrysanthemums.