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

Authors

  • Xiaofei Zhang 1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310032, Zhejiang, China
  • Yi Xun 1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310032, Zhejiang, China 2. Taizhou Key Laboratory of Advanced Manufacturing Technology, Taizhou Institute, Zhejiang University of Technology, Taizhou, 318014, Zhejiang, China
  • Qinghua Yang 3. College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 310032, Zhejiang, China 4. The Collaborative Innovation Center for Intelligent Production Equipment of Characteristic Forest Fruits in Hilly and Mountainous Areas of Zhejiang Province, Zhejiang A&F University, Hangzhou 310032, Zhejiang, China
  • Zhiheng Wang 1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310032, Zhejiang, China 2. Taizhou Key Laboratory of Advanced Manufacturing Technology, Taizhou Institute, Zhejiang University of Technology, Taizhou, 318014, Zhejiang, China

DOI:

https://doi.org/10.25165/ijabe.v18i3.9308

Keywords:

harvesting robot, apple, negative pressure adsorption, field trial

Abstract

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. Keywords: harvesting robot, apple, negative pressure adsorption, field trial. DOI: 10.25165/j.ijabe.20251803.9308 Citation: Zhang X F, Xun Y, Yang Q H, Wang Z H. Design and experiment of the negative pressure adsorption Cartesian robot system for apple harvesting. Int J Agric & Biol Eng, 2025; 18(3): 145–153.

References

Cheng J L, Guo W C, Zhang Z Y, Zeng S C, Wang Z W. Optical properties of ‘Gala’（Malus pumila） apple pulp and their relationship with internal quality. Infrared Physics & Technology, 2022; 123: 104210. DOI: 10.1016/j.infrared.2022.104210

Zhao X, Cao G H, Zhang P F, Ma Z H, Zhao L J, Chen J N. Dynamic analysis and lightweight design of 3-DOF apple picking manipulator. Transactions of the CSAM, 2023; 54（7）: 88–98. （in Chinese） DOI: 10. 6041/j. issn. 1000-1298.2023.07.009

Chen Q, Yin C K, Guo Z L, Wang J P, Zhou H P, Jiang X S. Current status and future development of the key technologies for apple picking robots. Transactions of the CSAE, 2023; 39（4）: 1–15. （in Chinese） DOI: 10.11975/j.issn.1002-6819.202209041

Fei Z H, Vougioukas S G. A robotic orchard platform increases harvest throughput by controlling worker vertical positioning and platform speed. Computers and Electronics in Agriculture, 2024; 218: 108735. DOI: 10.1016/j.compag.2024.108735

Liu C L, Gong L, Yuan J, Li Y M. Current status and development trends of agricultural robots. Transactions of the CSAM, 2022; 53（07）: 1–22, 55. （in Chinese） DOI: 10.6041/j. issn. 1000-1298.2022.07.001

Zhao Y X, Wan X F, Duo H X. Review of rigid fruit and vegetable picking robots. Int J Agric & Biol Eng, 2023; 16（5）: 1–11. DOI: 10.25165/j.ijabe.20231605.8120

Jia W K, Zhang Y, Lian J, Zheng Y J, Zhao D, Li C J. Apple harvesting robot under information technology: A review. International Journal of Advanced Robotic Systems, 2020; 17（3）. DOI: 10.1177/1729881420925310

Barbosa Júnior M R, Santos R G, Sales L A, Oliveira L P. Advancements in Agricultural Ground Robotsfor Specialty Crops: An Overview of Innovations, Challenges, and Prospects. Plants, 2024; 13（23）: 3372. DOI: 10.3390/plants13233372

Pi J, Liu J, Zhou K H, Qian M Y. An octopus-inspired bionic flexible gripper for apple grasping. Agriculture, 2021; 11（10）: 1014. DOI: 10.3390/agriculture11101014

Chen K W, Li T, Yan T J, Xie F, Feng Q C, Zhu Q Z, Zhao C J. A soft gripper design for apple harvesting with force feedback and fruit slip detection. Agriculture, 2022; 12（11）: 1802. DOI: 10.3390/agriculture12111802

Ji W, He G Z, Xu B, Zhang H W, Yu X W. A new picking pattern of a flexible three-fingered end-effector for apple harvesting robot. Agriculture, 2024; 14（1）: 102. DOI: 10.3390/agriculture14010102

Wang M R, Yan B, Zhang S H, Fan P, Zeng P Z, Shi S Q, Yang F Z. Development of a novel biomimetic mechanical hand based on physical characteristics of apples. Agriculture, 2022; 12（11）: 1871. DOI: 10.3390/agriculture12111871

Zhang Z, Zhou J, Yi B Y, Zhang B H, Wang K. A flexible swallowing gripper for harvesting apples and its grasping force sensing model. Computers and Electronics in Agriculture, 2023; 204: 107489. DOI: 10.1016/j.compag.2022.107489

Wang X, Kang H W, Zhou H Y, Au W, Wang M Y, Chen C. Development and evaluation of a robust soft robotic gripper for apple harvesting. Computers and Electronics in Agriculture, 2023; 204: 107552. DOI: 10.1016/j.compag.2022.107552

Fan P, Lang G D, Guo P J, Liu Z J, Yang F Z, Yan B, Lei X Y. Multi-feature patch-based segmentation technique in the gray-centered RGB color space for improved apple target recognition. Agriculture, 2021; 11（3）: 273. DOI: 10.3390/agriculture11030273

Wang D, He D. Fusion of Mask RCNN and attention mechanism for instance segmentation of apples under complex background. Computers and Electronics in Agriculture, 2022; 196: 106864. DOI: 10.1016/j.compag.2022.106864

Tang S X, Xia Z L, Gu J N, Wang W B, Huang Z D, Zhang W H. High-precision apple recognition and localization method based on RGB-D and improved SOLOv2 instance segmentation. Frontiers in Sustainable Food Systems, 2024; 8: 1403872. DOI: 10.1016/j.compag.2023.107952

Yan B, Fan P, Wang M R, Shi S Q, Lei X Y, Yang F Z. Real-time Apple Picking Pattern Recognition for Picking Robot Based on Improved YOLOv5m. Transactions of the CSAM, 2022; 53（09）: 28–38, 59. （in Chinese） DOI: 10.6041/j. issn. 1000-1298.2022.09.003

Zhou G H, M S, Liang F F. Recognition of the apple in panoramic images based on improved YOLOv4 model. Transactions of the CSAE, 2022; 38（21）: 159–168. （in Chinese） DOI: 10.11975/j.issn.1002-6819.2022.21.019

Wang J X, Su Y H, Yao J H, Liu M, Du Y R, Wu X, Huang L, Zhao M H. Apple rapid recognition and processing method based on an improved version of YOLOv5. Ecological Informatics, 2023; 77: 102196. DOI: 10.1016/j.ecoinf.2023.102196

Yan B, Li X M. RGB-D camera and fractal-geometry-based maximum diameter estimation method of apples for robot intelligent selective graded harvesting. Fractal and Fractional, 2024; 8（11）: 649. DOI: 10.3390/fractalfract8110649

Yang S, Wang H R, Wang G P, Wang J Z, Gu A G, Xue X M, Chen R. Effects of Seaweed-Extract-Based Organic Fertilizers on the Levels of Mineral Elements, Sugar–Acid Components and Hormones in Fuji Apples. Agronomy, 2023; 13（4）: 969. DOI: 10.3390/agronomy13040969

Yang S Z, Ji J C, Cai H X, Chen H. Modeling and force analysis of a harvesting robot for button mushrooms. IEEE Access, 2022; 10: 78519–78526. DOI: 10.1109/ACCESS.2022.3191802

Bottin M, Cipriani G, Tommasino D, Doria A. Analysis and control of vibrations of a Cartesian cutting machine using an equivalent robotic model. Machines, 2021; 9（8）: 162. DOI: 10.3390/machines9080162

D’Imperio S, Berruti T M, Gastaldi C, Soccio P. Tunable Vibration Absorber Design for a High-Precision Cartesian Robot. Robotics, 2022; 11（5）: 103. DOI: 10.3390/robotics11050103

Au C K, Barnett J, Lim S H, Duke M. Workspace analysis of Cartesian robot system for kiwifruit harvesting. Industrial Robot: the international journal of robotics research and application, 2020; 47（4）: 503–510. DOI: 10.1108/IR-12-2019-0255

Feng Q C, Zhao C J, Li T, Chen L P, Guo X, Xie F, Xiong Z C, Chen K W, Liu C, Yan T J. Design and test of a four-arm apple harvesting robot. Transactions of the CSAE, 2023; 39（13）: 25–33. （in Chinese） DOI: 10.11975/j.issn.1002-6819.202305114

Kirillov A, Mintun E, Ravi N, Mao H Z, Rolland C, Gustafson L, Xiao T T, Whitehead S, C. Berg A, Lo W Y, Dollár P, Girshick R. Segment anything. Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023; 4015-4026. DOI: 10.48550/arXiv.2304.02643

Hu G R, Chen C, Chen J, Sun L J, Sugirbay A, Chen Y, Jin H L, Zhang S, Bu L X. Simplified 4-DOF manipulator for rapid robotic apple harvesting. Computers and Electronics in Agriculture, 2022; 199: 107177. DOI: 10.1016/j.compag.2022.107177

Zhang K X, Lammers K, Chu P Y, Li Z J, Lu R F. An automated apple harvesting robot—From system design to field evaluation. Journal of Field Robotics, 2024; 41（7）: 2384–2400. DOI: 10.1002/rob.22268

Bu L X, Chen C K, Hu G R, Sugirbay A, Sun H X, Chen J. Design and evaluation of a robotic apple harvester using optimized picking patterns. Computers and Electronics in Agriculture, 2022; 198: 107092. DOI: 10.1016/j.compag.2022.107092

Huang W L, Miao Z H, Wu T, Guo Z W, Han W K, Li T. Design of and experiment with a dual-arm apple harvesting robot system. Horticulturae, 2024; 10（12）: 1268. DOI: 10.3390/horticulturae10121268

Downloads

Published

2025-06-30

How to Cite

Zhang, X., Xun, Y., Yang, Q., & Wang, Z. (2025). Design and experiment of the negative pressure adsorption Cartesian robot system for apple harvesting. International Journal of Agricultural and Biological Engineering, 18(3), 145–153. https://doi.org/10.25165/ijabe.v18i3.9308

Issue

Vol. 18 No. 3 (2025): IJABE

Section

Power and Machinery Systems

License

IJABE is an international peer reviewed open access journal, adopting Creative Commons Copyright Notices as follows.


Authors who publish with this journal agree to the following terms:


  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).