Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
126 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

DexiTac: Soft Dexterous Tactile Gripping (2405.02897v1)

Published 5 May 2024 in cs.RO

Abstract: Grasping object,whether they are flat, round, or narrow and whether they have regular or irregular shapes,introduces difficulties in determining the ideal grasping posture, even for the most state-of-the-art grippers. In this article, we presented a reconfigurable pneumatic gripper with fingers that could be set in various configurations, such as hooking, supporting, closuring, and pinching. Each finger incorporates a dexterous joint, a rotating joint, and a customized plug-and-play visuotactile sensor, the DigiTac-v1.5, to control manipulation in real time. We propose a tactile kernel density manipulation strategy for simple and versatile control, including detecting grasp stability, responding to disturbances and guiding dexterous manipulations. We develop a double closed-loop control system that separately focuses on secure grasping and task management, demonstrated with tasks that highlight the capabilities above. The gripper is relatively easy to fabricate and customize, offering a promising and extensible way to combine soft dexterity and tactile sensing for diverse applications in robotic manipulation.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (34)
  1. Y. Sun et al., “Research challenges and progress in robotic grasping and manipulation competitions,” IEEE robotics and automation letters, vol. 7, no. 2, pp. 874–881, 2021.
  2. S. E. Navarro et al., “Proximity perception in human-centered robotics: A survey on sensing systems and applications,” IEEE Transactions on Robotics, vol. 38, no. 3, pp. 1599–1620, 2022.
  3. T. Nishimura et al., “Lightweight high-speed and high-force gripper for assembly,” IEEE/ASME Transactions on Mechatronics, 2023.
  4. E. Ottonello et al., “Design and validation of a push-latch gripper made in additive manufacturing,” IEEE/ASME Transactions on Mechatronics, 2023.
  5. I. I. Borisov et al., “Reconfigurable underactuated adaptive gripper designed by morphological computation,” in 2022 International Conference on Robotics and Automation (ICRA).   IEEE, 2022, pp. 1130–1136.
  6. Z. Zhang et al., “Pneumatically controlled reconfigurable bistable bionic flower for robotic gripper,” Soft Robotics, vol. 9, no. 4, pp. 657–668, 2022.
  7. P. Cheng et al., “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.
  8. Y. Hao and Y. Visell, “Beyond soft hands: Efficient grasping with non-anthropomorphic soft grippers,” Frontiers in Robotics and AI, vol. 8, 2021.
  9. Y. Su et al., “A high-payload proprioceptive hybrid robotic gripper with soft origamic actuators,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 3003–3010, 2020.
  10. Z. Lu et al., “Gtac-gripper: A reconfigurable under-actuated four-fingered robotic gripper with tactile sensing,” IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7232–7239, 2022.
  11. S. Park et al., “Magtac: Magnetic six-axis force/torque fingertip tactile sensor for robotic hand applications,” in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023, pp. 10 367–10 372.
  12. A. Grover et al., “Under pressure: Learning to detect slip with barometric tactile sensors,” 2022.
  13. O. Leslie et al., “A tactile sensing concept for 3-d displacement and 3-d force measurement using light angle and intensity sensing,” IEEE Sensors Journal, vol. 23, no. 18, pp. 21 172–21 188, 2023.
  14. O. Leslie et al., “Design, fabrication, and characterization of a novel optical six-axis distributed force and displacement tactile sensor for dexterous robotic manipulation,” Sensors, vol. 23, no. 24, 2023.
  15. K. Shimonomura, “Tactile image sensors employing camera: A review,” Sensors, vol. 19, no. 18, 2019.
  16. U. H. Shah et al., “On the design and development of vision-based tactile sensors,” Journal of Intelligent & Robotic Systems, vol. 102, pp. 1–27, 2021.
  17. W. Yuan et al., “Gelsight: High-resolution robot tactile sensors for estimating geometry and force,” Sensors, vol. 17, no. 12, p. 2762, 2017.
  18. E. Donlon et al., “Gelslim: A high-resolution, compact, robust, and calibrated tactile-sensing finger,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 1927–1934.
  19. M. Lambeta et al., “Digit: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation,” IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 3838–3845, 2020.
  20. B. Ward-Cherrier et al., “The tactip family: Soft optical tactile sensors with 3d-printed biomimetic morphologies,” Soft robotics, vol. 5, no. 2, pp. 216–227, 2018.
  21. J. van Beesel et al., “Exploring the functional morphology of the gorilla shoulder through musculoskeletal modelling,” Journal of Anatomy, vol. 239, no. 1, pp. 207–227, 2021.
  22. S. Burgess, “A review of linkage mechanisms in animal joints and related bioinspired designs,” Bioinspiration & Biomimetics, vol. 16, no. 4, p. 041001, 2021.
  23. N. F. Lepora et al., “Digitac: A digit-tactip hybrid tactile sensor for comparing low-cost high-resolution robot touch,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 9382–9388, 2022.
  24. W. Zhu et al., “A soft-rigid hybrid gripper with lateral compliance and dexterous in-hand manipulation,” IEEE/ASME Transactions on Mechatronics, vol. 28, no. 1, pp. 104–115, 2022.
  25. H. Bay et al., “Surf: Speeded up robust features,” in Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006. Proceedings, Part I 9.   Springer, 2006, pp. 404–417.
  26. R. J. Webster III and B. A. Jones, “Design and kinematic modeling of constant curvature continuum robots: A review,” The International Journal of Robotics Research, vol. 29, no. 13, pp. 1661–1683, 2010.
  27. K. Tang et al., “A strong underwater soft manipulator with planarly-bundled actuators and accurate position control,” IEEE Robotics and Automation Letters, 2023.
  28. M. Otaki and K. Shibata, “The effect of different visual stimuli on reaction times: a performance comparison of young and middle-aged people,” Journal of physical therapy science, vol. 31, no. 3, pp. 250–254, 2019.
  29. H. R. Heekeren et al., “The neural systems that mediate human perceptual decision making,” Nature reviews neuroscience, vol. 9, no. 6, pp. 467–479, 2008.
  30. Q. Lu et al., “Systematic object-invariant in-hand manipulation via reconfigurable underactuation: Introducing the ruth gripper,” The International Journal of Robotics Research, vol. 40, no. 12-14, pp. 1402–1418, 2021.
  31. J. W. James et al., “Tactile model o: Fabrication and testing of a 3d-printed, three-fingered tactile robot hand,” Soft Robotics, vol. 8, no. 5, pp. 594–610, 2021.
  32. J. H. Low et al., “Sensorized reconfigurable soft robotic gripper system for automated food handling,” IEEE/ASME Transactions on Mechatronics, vol. 27, no. 5, pp. 3232–3243, 2022.
  33. B. Ward-Cherrier et al., “Tactile manipulation with a tacthumb integrated on the open-hand m2 gripper,” IEEE Robotics and Automation Letters, vol. 1, no. 1, pp. 169–175, 2016.
  34. B. Ward-Cherrier et al., “Model-free precise in-hand manipulation with a 3d-printed tactile gripper,” IEEE Robotics and Automation Letters, vol. 2, no. 4, pp. 2056–2063, 2017.
Citations (2)

Summary

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