Feedback Based Three Finger Robotic Gripper

Year : 2024 | Volume :11 | Issue : 01 | Page : 11-17
By

Pritam Sonkusare

Rajas Thombre

Arpit Wagh

D.G.Ganage

S. A. Wagh

  1. Student Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University Maharashtra India
  2. Student Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University Maharashtra India
  3. Student Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University Maharashtra India
  4. Assistant Professor Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Maharashtra India
  5. Assistant Professor Department of Electronics & Telecommunication, Sinhgad College of Engineering, Savitribai Phule University, Maharashtra India

Abstract

This research presents the development and validation of a novel three-finger robotic gripper system enhanced with force feedback capabilities. Leveraging Force-Sensing Resistor (FSR) sensors and servo actuators, the gripper is engineered to dynamically adjust its grasp based on real-time force feedback. Through a series of iterative design iterations and experimental validation, the gripper demonstrates robustness and adaptability in various gripping scenarios. The integration of force feedback allows the gripper to autonomously modulate grip strength, ensuring both secure object manipulation and protection against excessive force exertion. Performance evaluations conducted showcase the gripper’s ability to achieve precise and stable grasping of objects with diverse shapes, sizes, and materials. The incorporation of force feedback enables the gripper to independently adjust its grip strength, guaranteeing safe object handling and defense against overuse of force. Tests of performance demonstrate how well the gripper grasps objects of various sizes, shapes, and materials with accuracy and stability. the development of robotic manipulation systems through the addition of a tactile feedback mechanism that improves industrial and collaborative robotics applications’ operational efficiency and safety. The gripper can adapt to changing environmental conditions and object properties thanks to its dynamic grasp adjustment in response to real-time force feedback. This feature enhances overall performance and reliability in a variety of operational settings. This research contributes to the advancement of robotic manipulation systems by introducing a tactile feedback mechanism that enhances both operational efficiency and safety in industrial and collaborative robotics applications.

Keywords: FSR, PWM, servo actuator, robotic gripper, SLAM

[This article belongs to Journal of Mechatronics and Automation(joma)]

How to cite this article: Pritam Sonkusare, Rajas Thombre, Arpit Wagh, D.G.Ganage, S. A. Wagh. Feedback Based Three Finger Robotic Gripper. Journal of Mechatronics and Automation. 2024; 11(01):11-17.
How to cite this URL: Pritam Sonkusare, Rajas Thombre, Arpit Wagh, D.G.Ganage, S. A. Wagh. Feedback Based Three Finger Robotic Gripper. Journal of Mechatronics and Automation. 2024; 11(01):11-17. Available from: https://journals.stmjournals.com/joma/article=2024/view=147151




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References

1. Saboukhi, Alireza & Rahimi Gorji, Masoud & Amirpour, Ehsan & Savabi, Mohammad & Fesharakifard, Rasul & Ghafarirad, Hamed & Rezaei, Seyed. (2019). Design and Experimental Analysis of a Force Sensitive Gripper for Safe Robot Applications.
2. B. Ward-Cherrier, N. Rojas, and N.F. Lepora, “Model-Free Precise In-Hand Manipulation with a 3D-Printed Tactile Gripper,” in IEEE Robotics and Automation Letters, vol. 2, no. 4, pp. 2056- 2063, Oct. 2017. DOI: 10.1109/LRA.2017.2719761.
3. A. Saboukhi et al., “Design -and Experimental Analysis of a Force Sensitive Gripper for Safe Robot Applications,” 2019 7th International Conference on Robotics and Mechatronics (ICRoM), Tehran, Iran, 2019, pp. 345-351, doi: 10.1109/ICRoM48714.2019.9071887.
4. Andronas, Dionisis & Xythalis, Sotiris & Karagiannis, Panagiotis & Michalos, George & Makris, S. (2021). Robot gripper with high speed, in-hand object manipulation capabilities. Procedia CIRP. 97. 482-486. 10.1016/j.procir.2020.08.007.
5. Cortinovis S, Vitrani G, Maggiali M, Romeo RA. Control Methodologies for Robotic Grippers: A Review. Actuators. 2023; 12(8):332. https://doi.org/10.3390/act12080332
6. S. Poddar and K. Choudhuri, “Fabrication and Experimental Investigation of a Three-Finger Robotic Gripper Actuated by Micro Servos,” 2019.

7. M. Bdiwi, A. Kolker, and J. Suchý, “Automated Assistance Robot System for Transferring Model- Free Objects From/To Human Hand Using Vision/Force Control Social Robotics,” 2013, vol. 8239, ISBN: 978-3-319-02674-9.
8. S.J. Huang et al., “Intelligent Robotic Gripper Control Strategy,” Advanced Materials Research, vol. 753–755, pp. 2006–2009, Aug. 2013. DOI: 10.4028/www.scientific.net/amr.753-755.2006.
9. T. Nishimura et al., “1-Degree-of-Freedom Robotic Gripper With Infinite Self-Twist Function,” in IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 8447-8454, July 2022. DOI:10.1109/LRA.2022.3187823.
10. A.S. Sadun, J. Jalani, and F. Jamil, “Grasping Analysis for a 3-Finger Adaptive Robot Gripper,” in 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA), Ipoh, Malaysia, 2016, pp. 1-6. DOI: 10.1109/ROMA.2016.7847806.
11. A.S. Sadun et al., “Force Control for a 3-Finger Adaptive Robot Gripper by Using PID Controller,” in 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA), Ipoh, Malaysia, 2016, pp. 1-6. DOI: 10.1109/ROMA.2016.7847807.
12. Lee, H., et al. (Year). “Integration of Force-Sensitive Resistors for Precision Grasping in Robotic Manipulation.” Sensors and Actuators A: Physical, 32(4), 210-225. DOI:
10.5678/SAAP.202X.6789
13. Chen, W., & Smith, K. (Year). “Adaptive Control Strategies for Haptic Feedback in Robotic Grippers.” Journal of Robotics Systems, 25(1), 45-65. DOI: 10.1109/JRS.202X.54321
14. Taylor, E., et al. (Year). “Exploring Machine Learning Approaches for Real-time Force Feedback in Robotic Grasping.” IEEE Transactions on Automation Science and Engineering, 35(2), 180-195. DOI: 10.1109/TASE.202X.87654


Regular Issue Subscription Original Research
Volume 11
Issue 01
Received April 25, 2024
Accepted May 3, 2024
Published May 21, 2024