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Study of the influence of robotic gripper parameters on apple fruit damage

https://doi.org/10.31676/0235-2591-2024-1-40-50

EDN: ypqafo

Abstract

   The article discusses the design of a robotic device intended for effective apple fruit harvesting with minimum damage. The research was conducted in the Federal Scientific Agroengineering Center VIM from 2020 to 2023. The developed device is equipped with specialized mechanisms and sensors designed to reduce the negative eff ects on apples during harvesting.

   The study aims to justify the parameters of the robotic device for apple fruit picking and to conduct laboratory experimental studies of the grip strength eff ect on fruit damage during robotic fruit harvesting.

   A classification of gripping devices was developed based on the analysis of their design parameters and types. A concentric three-fingered gripper tool with rotating and sliding elements added to the gripping device was selected as the prototype device. As a result of studying the size and weight parameters of apples of the ‘Jonathan’ and ‘Granny Smith’ cultivars, data were obtained that enable one to describe the characteristics of these fruits more fully. Th e grapho-analytical method was employed to select the optimal geometric parameters of the gripper claws. We designed a robotic gripper which has several components, including gripper claws and a movable base. A laboratory setup was developed to simulate the operation of the manipulator and conduct experiments. Th e setup makes it possible to create conditions close to the actual manipulator operation and study the processes of grasping and holding fruits. The three-factor experiment allowed us to analyze the impact of the grip strength of the gripper claws, as well as the distance from the fruit to the gripper on the damage to fruits. It has been determined that these parameters have a signifi cant eff ect on the process of grasping and holding fruits. Entirely optimal values of these parameters contribute to reliable holding of a fruit in the gripper claws with minimal damage. As a result of analyzing the size-mass parameters of fruits, we found the average size and weight of apples of the Jonathan and Granny Smith cultivars. Th e design parameters of the robotic device were justifi ed. A 3D robotic gripper model was developed. We also manufactured an experimental robotic gripper model which underwent laboratory tests. As a result, the parameters of the grip strength and the distance from the fruit to the gripper were identified.

About the Authors

D. S. Pupin
Federal Scientific Agroengineering Center VIM
Russian Federation

Graduate Student, Junior Research

Moscow



D. O. Khort
Federal Scientific Agroengineering Center VIM
Russian Federation

Dmitry O. Khort, Dr. Sci. (Tech.), Leading Researcher

109428; 1st Institute Passage, 5; Moscow



References

1. Li Z. & Zhu C. Adaptive robotic grasp control with deep reinforcement learning. IEEE Robotics and Automation Letters. 2019, 3529-3536.

2. Song Y., Wang Y., Jin Y., Luo L., Xu H. & Zhang J. Advances in robotic grasping and manipulation : a survey. Engineering Reports. 2020, 234-241.

3. Faegh Z., Wan, Y. & Khedekar P. Robotic Grasping with Tactile Sensing : A Review. Robotics. 2021, 50 р.

4. Della Santina C., Catalano M. G., Grioli G., Garabini M. & Bicchi A. The Pisa/IIT Soft Hand: A 3D-printed anthropomorphic robot hand. IEEE Robotics and Automation Letters. 2021, 6125-6132.

5. Khort D. O., Kutyrev A. I., Filippov R. A., Vershinin R. V. Device for robotic picking of strawberries. E3S Web of Conferences. International Conference on Modern Trends in Manufacturing Technologies and Equipment (ICMTMTE 2020). 2020, 01045 р.

6. Khort D. O., Smirnov I. G., Kutyrev A. I., Baranov V. N. Development of an automated weather complex for managing agricultural technologies in horticulture. E3S Web of Conferences. International Conference on ModerPrograms. Moscow: Separate Edition, 2019, 125 р.

7. Gubanov S. G. Fundamentals of modeling in Fusion 360. M.: Dodéka XXI, 2019, 11 р.

8. Xu Y., Mei Y., Zhang J., & Li Z. A review of robotic grasping and manipulation. Mechatronics. 2022, 74 р.

9. Chetvertakov A. V. Technological processes and means of mechanization of transportation and commercial processing of fruits. M. : Dissertation of Doctor of Technical Sciences, Moscow, 1994, 61 p.

10. Khort D. O. Digital and technical solutions for intensive horticulture. M. : Abstract of Doctor of Technical Sciences dissertation, Moscow, 2022, 34 p.

11. Le A. T. & Ng K. H. Updated review of robotic grippers design and control for pick-and-place operations. Robotica. 2021, 2049-2081.

12. Smith J. & Johnso A. Advances in Integrated Circuit Design. Journal of Electronics and Circuit Design. 2021;45(2):123-135.

13. Brown L. A. & Davis M. A Comparative Study of Digital Logic Gates. International Journal of Electrical Engineering. 2020, 567-578.

14. Patel R. & Williams S. Design and Analysis of Low-Power CMOS Circuits. Journal of VLSI Design. 2021, 89-102.

15. Garcia C. Analog Circuit Design Techniques for High-Frequency Applications. IEEE Transactions on Circuits and Systems, 2021, 456-468.

16. Zhang Q. & Wang L. A Survey on Emerging Trends in Integrated Circuit Design. Journal of Electronic Systems. 2022, 234-247.

17. Wang Y. & Liu Z. Advanced Techniques for Power Management in Integrated Circuits. IEEE Transactions on Power Electronics. 2022;38(6):1234-1246.

18. Baohua Zhang. State-of-the-art robotic grippers, grasping and control strategies, as well as their applications in agricultural robots. М.: Computers and Electronics in Agriculture, 2020, 177.

19. Rukhovets I. I. Fundamentals of control theory. M.: Yurayt, 2019, 13 р.

20. Zhang Z. A Flexible New Technique for Camera Calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2021, 1330-1334.

21. Zhiqiang W. System for the Direct Monitoring of Biological Objects in an Ecologically Balanced Zone Drones. Computers and Electronics in Agriculture. 2023, 33 р.

22. Kulikov S. M., Smaglov V. A. Electric drives. Control and regulation. M.: Higher School, 2019, 33 р.

23. Wu A., Zhu Z., Ren T. Detection of apple defect using laser-induced light backscattering imaging and convolutional neural network. Computers & Electrical Engineering. 2020, 4-6 р.


Review

For citations:


Pupin D.S., Khort D.O. Study of the influence of robotic gripper parameters on apple fruit damage. Horticulture and viticulture. 2024;(1):40-50. (In Russ.) https://doi.org/10.31676/0235-2591-2024-1-40-50. EDN: ypqafo

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ISSN 0235-2591 (Print)
ISSN 2618-9003 (Online)