Selective Harvesting

Selective harvesting, the automated picking of ripe produce while leaving unripe items untouched, aims to increase agricultural efficiency and reduce waste. Current research focuses on developing robotic systems with advanced perception capabilities (often employing deep learning models like YOLO and customized architectures for improved speed and accuracy), sophisticated grippers capable of gentle yet secure handling of diverse produce, and efficient motion planning algorithms to navigate complex plant structures. These advancements hold significant promise for addressing labor shortages in agriculture and optimizing crop yields, particularly in high-value crops like strawberries and tea.