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Automatic Fingerpad Customization for Precise and Stable Grasping of 3D-Print Parts

Published 28 Mar 2024 in cs.RO | (2403.19102v1)

Abstract: The rise in additive manufacturing comes with unique opportunities and challenges. Massive part customization and rapid design changes are made possible with additive manufacturing, however, manufacturing industries that desire the implementation of robotics automation to improve production efficiency could face challenges in the gripper design and grasp planning due to highly complex geometrical shapes resulting from massive part customization. Yet, current gripper design for such objects are often manual and rely on ad-hoc design intuition. This would be limiting as such grippers would lack the ability to grasp different objects or grasp points, which is important for practical implementations. Hence, we introduce a fast, end-to-end approach to customize rigid gripper fingerpads that could achieve precise and stable grasping for different objects at multiple grasp points. Our approach relies on two key components: (i) a method based on set Boolean operations, e.g. intersections, subtractions, and unions to extract object features and synthesize gripper surfaces that conform to different local shapes to form caging grasps; (ii) a method to evaluate the grasp quality of synthesized grippers. We experimentally demonstrate the validity of our approach by synthesizing fingerpads that, once mounted on a physical robot gripper, are able to grasp different objects at multiple grasp points, all with tightly constrained grasps.

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References (46)
  1. R. Goel and P. Gupta, “Robotics and industry 4.0,” A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development, pp. 157–169, 2020.
  2. G. Fantoni, M. Santochi, G. Dini, K. Tracht, B. Scholz-Reiter, J. Fleischer, T. K. Lien, G. Seliger, G. Reinhart, J. Franke et al., “Grasping devices and methods in automated production processes,” CIRP Annals, vol. 63, no. 2, pp. 679–701, 2014.
  3. M. Honarpardaz, J. Ölvander, and M. Tarkian, “Fast finger design automation for industrial robots,” Robotics and Autonomous Systems, vol. 113, pp. 120–131, 2019.
  4. M. Honarpardaz, M. Tarkian, X. Feng, D. Sirkett, and J. Ölvander, “Generic automated finger design,” in International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol. 50169.   American Society of Mechanical Engineers, 2016, p. V05BT07A071.
  5. D. T. Pham, N. S. Gourashi, and E. E. Eldukhri, “Automated configuration of gripper systems for assembly tasks,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 221, no. 11, pp. 1643–1649, 2007.
  6. L. Balan and G. M. Bone, “Automated gripper jaw design and grasp planning for sets of 3d objects,” Journal of Robotic Systems, vol. 20, no. 3, pp. 147–162, 2003.
  7. V. Velasco and W. S. Newman, “Computer-assisted gripper and fixture customization using rapid-prototyping technology,” in Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No. 98CH36146), vol. 4.   IEEE, 1998, pp. 3658–3664.
  8. J. Mahler, R. Platt, A. Rodriguez, M. Ciocarlie, A. Dollar, R. Detry, M. A. Roa, H. Yanco, A. Norton, J. Falco et al., “Guest editorial open discussion of robot grasping benchmarks, protocols, and metrics,” IEEE Transactions on Automation Science and Engineering, vol. 15, no. 4, pp. 1440–1442, 2018.
  9. Q. Liu, X. Gu, N. Tan, and H. Ren, “Soft robotic gripper driven by flexible shafts for simultaneous grasping and in-hand cap manipulation,” IEEE Transactions on Automation Science and Engineering, vol. 18, no. 3, pp. 1134–1143, 2021.
  10. V. Wall, G. Zöller, and O. Brock, “A method for sensorizing soft actuators and its application to the rbo hand 2,” IEEE International Conference on Robotics and Automation (ICRA), pp. 4965–4970, 2017.
  11. J. Xu, T. Aykut, D. Ma, and E. Steinbach, “6dls: Modeling nonplanar frictional surface contacts for grasping using 6-d limit surfaces,” IEEE Transactions on Robotics, 2021.
  12. T. Hou, X. Yang, Y. Aiyama, K. Liu, Z. Wang, T. Wang, J. Liang, and Y. Fan, “Design and experiment of a universal two-fingered hand with soft fingertips based on jamming effect,” Mechanism and Machine Theory, vol. 133, pp. 706–719, 2019.
  13. E. Brown, N. Rodenberg, J. Amend, A. Mozeika, E. Steltz, M. R. Zakin, H. Lipson, and H. M. Jaeger, “Universal robotic gripper based on the jamming of granular material,” Proceedings of the National Academy of Sciences, vol. 107, no. 44, pp. 18 809–18 814, 2010.
  14. C. Pacchierotti, F. Ongaro, F. Van Den Brink, C. Yoon, D. Prattichizzo, D. H. Gracias, and S. Misra, “Steering and control of miniaturized untethered soft magnetic grippers with haptic assistance,” IEEE transactions on automation science and engineering, vol. 15, no. 1, pp. 290–306, 2017.
  15. H. Song, M. Y. Wang, and K. Hang, “Fingertip surface optimization for robust grasping on contact primitives,” IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 742–749, 2018.
  16. A. Bicchi, “On the closure properties of robotic grasping,” The International Journal of Robotics Research, vol. 14, no. 4, pp. 319–334, 1995.
  17. M. A. Roa and R. Suárez, “Grasp quality measures: review and performance,” Autonomous robots, vol. 38, no. 1, pp. 65–88, 2015.
  18. H. Ha, S. Agrawal, and S. Song, “Fit2form: 3d generative model for robot gripper form design,” in Conference on Robot Learning.   PMLR, 2021, pp. 176–187.
  19. F. Alet, M. Bauza, K. J. Adarsh, M. Thomsen, A. Rodriguez, L. P. Kaelbling, and T. Lozano-Pérez, “Robotic gripper design with evolutionary strategies and graph element networks,” in NeurIPS Workshop on Machine Learning for Engineering Modeling, Simulation, and Design, vol. 23, 2020.
  20. B. Calli, A. Singh, A. Walsman, S. Srinivasa, P. Abbeel, and A. M. Dollar, “The ycb object and model set: Towards common benchmarks for manipulation research,” in 2015 International Conference on Advanced Robotics (ICAR), 2015, pp. 510–517.
  21. W. Park, S. Seo, and J. Bae, “A hybrid gripper with soft material and rigid structures,” IEEE Robotics and Automation Letters, vol. 4, no. 1, pp. 65–72, 2019.
  22. R. Ma and A. Dollar, “Yale openhand project: Optimizing open-source hand designs for ease of fabrication and adoption,” IEEE Robotics & Automation Magazine, vol. 24, no. 1, pp. 32–40, 2017.
  23. V. V. Patel and A. M. Dollar, “Robot hand based on a spherical parallel mechanism for within-hand rotations about a fixed point,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2021, pp. 709–716.
  24. Z. Flintoff, B. Johnston, and M. Liarokapis, “Single-grasp, model-free object classification using a hyper-adaptive hand, google soli, and tactile sensors,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2018, pp. 1943–1950.
  25. X. Li, W. Chen, W. Lin, and K. H. Low, “A variable stiffness robotic gripper based on structure-controlled principle,” IEEE Transactions on Automation Science and Engineering, vol. 15, no. 3, pp. 1104–1113, 2018.
  26. Q. Xu, “Design and development of a novel compliant gripper with integrated position and grasping/interaction force sensing,” IEEE Transactions on Automation Science and Engineering, vol. 14, no. 3, pp. 1415–1428, 2015.
  27. C. Ferrari and J. F. Canny, “Planning optimal grasps.” in ICRA, vol. 3, no. 4, 1992, p. 6.
  28. S. Makita and W. Wan, “A survey of robotic caging and its applications,” Advanced Robotics, vol. 31, no. 19-20, pp. 1071–1085, 2017. [Online]. Available: https://doi.org/10.1080/01691864.2017.1371075
  29. J. Ruan, H. Liu, A. Xue, X. Wang, and B. Liang, “Grasp quality evaluation network for surface-to-surface contacts in point clouds,” in 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE).   IEEE, 2020, pp. 1467–1472.
  30. M. Danielczuk, J. Xu, J. Mahler, M. Matl, N. Chentanez, and K. Goldberg, “Reach: Reducing false negatives in robot grasp planning with a robust efficient area contact hypothesis model,” in International Symposium on Robotics Research (ISRR), 2019.
  31. J. Xu, M. Danielczuk, E. Steinbach, and K. Goldberg, “6dfc: Efficiently planning soft non-planar area contact grasps using 6d friction cones,” in 2020 IEEE International Conference on Robotics and Automation (ICRA).   IEEE, 2020, pp. 7891–7897.
  32. E. Rimon and A. Stappen, “Immobilizing 2-d serial chains in form-closure grasps,” IEEE Transactions on Robotics, vol. 28, no. 1, pp. 32–43, 2011.
  33. E. D. Rimon and A. Blake, “Caging 2d bodies by 1-parameter two-fingered gripping systems,” Proceedings of IEEE International Conference on Robotics and Automation, vol. 2, pp. 1458–1464 vol.2, 1996.
  34. E. Rimon and A. Blake, “Caging planar bodies by one-parameter two-fingered gripping systems,” The International Journal of Robotics Research, vol. 18, no. 3, pp. 299–318, 1999.
  35. P. Pipattanasomporn and A. Sudsang, “Two-finger caging of concave polygon,” IEEE International Conference on Robotics and Automation, vol. 2006, pp. 2137 – 2142, 06 2006.
  36. P. Peam, V. Pawin, and S. Attawith, “Two-finger squeezing caging of polygonal and polyhedral object,” IEEE International Conference on Robotics and Automation, pp. 205–210, 2007.
  37. ——, “Caging rigid polytopes via finger dispersion control,” IEEE International Conference on Robotics and Automation, pp. 1181–1186, 2008.
  38. K. Goldberg, B. V. Mirtich, Y. Zhuang, J. Craig, B. R. Carlisle, and J. Canny, “Part pose statistics: Estimators and experiments,” IEEE Transactions on Robotics and Automation, vol. 15, no. 5, pp. 849–857, 1999.
  39. A. T. Miller and P. K. Allen, “Graspit! a versatile simulator for robotic grasping,” IEEE Robotics & Automation Magazine, vol. 11, no. 4, pp. 110–122, 2004.
  40. M. Malvezzi, G. Gioioso, G. Salvietti, and D. Prattichizzo, “Syngrasp: A matlab toolbox for underactuated and compliant hands,” Robotics Automation Magazine, IEEE, vol. 22, no. 4, pp. 52–68, Dec 2015.
  41. J. Mahler, M. Matl, V. Satish, M. Danielczuk, B. DeRose, S. McKinley, and K. Goldberg, “Learning ambidextrous robot grasping policies,” Science Robotics, vol. 4, no. 26, p. eaau4984, 2019.
  42. A. Zeng, S. Song, K.-T. Yu, E. Donlon, F. R. Hogan, M. Bauza, D. Ma, O. Taylor, M. Liu, E. Romo et al., “Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching,” The International Journal of Robotics Research, vol. 41, no. 7, pp. 690–705, 2022.
  43. N. Aloysius and M. Geetha, “A review on deep convolutional neural networks,” in 2017 International Conference on Communication and Signal Processing (ICCSP).   IEEE, 2017, pp. 0588–0592.
  44. M. Caroli, P. M. de Castro, S. Loriot, O. Rouiller, M. Teillaud, and C. Wormser, “Robust and efficient delaunay triangulations of points on or close to a sphere,” in International Symposium on Experimental Algorithms.   Springer, 2010, pp. 462–473.
  45. M. Schuster, “The largest empty circle problem,” in Proceedings of the Class of 2008 Senior Conference, Computer Science Department, Swarthmore College, 2008, pp. 28–37.
  46. S. Maneewongvatana and D. M. Mount, “Analysis of approximate nearest neighbor searching with clustered point sets,” CoRR, vol. cs.CG/9901013, 1999. [Online]. Available: https://arxiv.org/abs/cs/9901013

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