Design and experiment of the negative pressure adsorption Cartesian robot system for apple harvesting

To address the limitation of low harvesting efficiency in intelligent mechanized harvesting in standardized orchards, a negative pressure adsorption apple harvesting robot has been designed and developed. The robot is based on a Cartesian coordinate system and incorporates direct negative pressure adsorption picking combined with multi-stage buffering collection methods. Additionally, the proposed model pipeline integrates YOLOv8 and Segment Anything Model for precise apple picking point localization. Finally, field trials of the apple harvesting robot were conducted in a V-shaped layout apple orchard at Experiment and Demonstration Orchard at Tianping Lake. The experimental results showed an apple recognition rate of 90.54%, an overall harvesting success rate of 83.65%, an average picking efficiency of 4.83 s per fruit, and a damage rate of 13.61%. It demonstrates the potential of the robot in improving the efficiency and reliability of automated apple harvesting. At the same time, the results highlight the need to focus on enhancing the robustness of apple recognition algorithms under varying lighting conditions, and reducing apple damage rates by shortening the transport pipeline and optimizing the structure of the collection device. This study provides a promising solution for addressing global challenges in agricultural automation, offering insights into the future optimization of intelligent harvesting technologies.