Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
140 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation (2410.22893v1)

Published 30 Oct 2024 in cs.RO

Abstract: Robotic manipulation of fresh fruits and vegetables, including the grasping of multiple loose items, has a strong industrial need but it still is a challenging task for robotic manipulation. This paper outlines the distinctive manipulation strategies used by humans to pick loose fruits and vegetables with the aim to better adopt them for robotic manipulation of diverse items. In this work we present a first version of a robotic setup designed to pick different single or multiple fresh items, featuring multi-fingered compliant robotic gripper. We analyse human grasping strategies from the perspective of industrial Key Performance Indicators (KPIs) used in the logistic sector. The robotic system was validated using the same KPIs, as well as taking into account human performance and strategies. This paper lays the foundation for future development of the robotic demonstrator for fresh fruit and vegetable intelligent manipulation, and outlines the need for generic approaches to handle the complexity of the task.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (25)
  1. K. Kleeberger, R. Bormann, W. Kraus, and M. Huber, “A Survey on Learning-Based Robotic Grasping,” Current Robotics Reports, vol. 1, p. 239–249, 12 2020.
  2. A. Saxena, J. Driemeyer, and A. Ng, “Robotic Grasping of Novel Objects using Vision,” International Journal of Robotic Research (IJRR), vol. 27, pp. 157–173, 02 2008.
  3. T. Feix, J. Romero, H.-B. Schmiedmayer, A. M. Dollar, and D. Kragic, “The GRASP Taxonomy of Human Grasp Types,” IEEE Transactions on Human-Machine Systems, vol. 46, no. 1, pp. 66–77, 2016.
  4. E. Grosse, C. Glock, and W. Neumann, “Human factors in order picking: A content analysis of the literature,” International Journal of Production Research, vol. 55, 05 2016.
  5. Y. Li, B. Liu, Y. Geng, P. Li, Y. Yang, Y. Zhu, T. Liu, and S. Huang, “Grasp Multiple Objects with One Hand,” IEEE Robotics and Automation Letters (RAL), vol. 9, no. 5, pp. 4027–4034, 2024.
  6. F.-J. Chu, R. Xu, and P. Vela, “Real-World Multiobject, Multigrasp Detection,” IEEE Robotics and Automation Letters (RAL), vol. PP, pp. 1–1, 07 2018.
  7. A. Billard and D. Kragic, “Trends and Challenges in Robot Manipulation,” Science, vol. 364, 06 2019.
  8. Y. Sun, E. Amatova, and T. Chen, “Multi-Object Grasping - Types and Taxonomy,” in IEEE International Conference on Robotics and Automation (ICRA), 2022, pp. 777–783.
  9. Z. Xu, W. Shi, D. Zhao, K. Li, J. Li, J. Dong, Y. Han, J. Zhao, and H. Yan, “Research Progress on Low Damage Grasping of Fruit, Vegetable and Meat Raw Materials,” Foods (Basel, Switzerland), vol. 12, 09 2023.
  10. S. Washio, K. Gilday, and F. Iida, “Design and Control of a Multi-modal Soft Gripper Inspired by Elephant Fingers,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2022, pp. 4228–4235.
  11. P. Cheng, Y. Lu, C. Wu, and B. Yan, “Reconfigurable Bionic Soft Pneumatic Gripper for Fruit Handling Based on Shape and Size Adaptation,” Journal of Physics D: Applied Physics, vol. 56, no. 4, p. 044003, 2022.
  12. Z. Wang, Y. Wu, J. Yang, H. Song, K. B. Dinh, D. Zhang, and V. K. Truong, “A Soft Gripper with Contamination Resistance and Large Friction Coefficient,” Applied Physics A, vol. 128, no. 5, p. 461, 2022.
  13. M. Baggetta, G. Hao, and G. Berselli, “Design and Virtual Prototyping of a Constant Force Gripper for Food Handling and Harvesting,” in International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol. 87295.   American Society of Mechanical Engineers, 2023, p. V002T02A024.
  14. A. E. Karadağ and A. Kılıç, “Non-destructive Robotic Sorting of Cracked Pistachio using Deep Learning,” Postharvest Biology and Technology, vol. 198, p. 112229, 2023.
  15. A. T. Mathew, I. Hussain, C. Stefanini, I. M. B. Hmida, and F. Renda, “ReSoft Gripper: A Reconfigurable Soft Gripper with Monolithic Fingers and Differential Mechanism for Versatile and Delicate Grasping,” in 2021 IEEE 4th International Conference on Soft Robotics (RoboSoft).   IEEE, 2021, pp. 372–378.
  16. W. Friedl and M. A. Roa, “CLASH—A Compliant Sensorized Hand for Handling Delicate Objects,” Frontiers in Robotics and AI, vol. 6, p. 138, 2020.
  17. Y. Makiyama, Z. Wang, and S. Hirai, “A Pneumatic Needle Gripper for Handling Shredded Food Products,” in 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR).   IEEE, 2020, pp. 183–187.
  18. H. Aoyama, Z. Wang, and S. Hirai, “Shell Gripper Inspired by Human Finger Structure for Automatically Packaging Agricultural Product,” in IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).   IEEE, 2022, pp. 90–95.
  19. EU IntelliMan: AI-Powered Manipulation System for Advanced Robotic Service, Manufacturing and Prosthetics. [Online]. Available: https://intelliman-project.eu
  20. P. Triantafyllou, H. Mnyusiwalla, P. Sotiropoulos, M. A. Roa, D. Russell, and G. Deacon, “A Benchmarking Framework for Systematic Evaluation of Robotic Pick-and-Place Systems in an Industrial Grocery Setting,” in IEEE International Conference on Robotics and Automation (ICRA), 2019, pp. 6692–6698.
  21. H.-I. Lin, C.-H. Cheng, and W.-K. Chen, “Learning a Pick-and-Place Robot Task from Human Demonstration,” in International Automatic Control Conference (CACS), 2013, pp. 312–317.
  22. A. León, E. Morales, L. Altamirano Robles, and J. Ruiz, “Teaching a Robot to Perform Task through Imitation and On-line Feedback,” in Springer Berlin Heidelberg, 11 2011, pp. 549–556.
  23. C.-A. Cheng, X. Yan, N. Wagener, and B. Boots, “Fast Policy Learning through Imitation and Reinforcement,” ArXiv, vol. abs/1805.10413, 2018. [Online]. Available: https://api.semanticscholar.org/CorpusID:44137801
  24. R. Ghzouli, T. Berger, E. B. Johnsen, D. Swaib, and A. Wasowski, “Behavior Trees in Action: A Study of Robotics Applications,” 10 2020.
  25. S. Macenski, T. Foote, B. Gerkey, C. Lalancette, and W. Woodall, “Robot Operating System 2: Design, Architecture, and Uses in the Wild,” Science Robotics, vol. 7, no. 66, p. eabm6074, 2022. [Online]. Available: https://www.science.org/doi/abs/10.1126/scirobotics.abm6074

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets