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A versatile robotic hand with 3D perception, force sensing for autonomous manipulation (2402.06018v1)

Published 8 Feb 2024 in cs.RO

Abstract: We describe a force-controlled robotic gripper with built-in tactile and 3D perception. We also describe a complete autonomous manipulation pipeline consisting of object detection, segmentation, point cloud processing, force-controlled manipulation, and symbolic (re)-planning. The design emphasizes versatility in terms of applications, manufacturability, use of commercial off-the-shelf parts, and open-source software. We validate the design by characterizing force control (achieving up to 32N, controllable in steps of 0.08N), force measurement, and two manipulation demonstrations: assembly of the Siemens gear assembly problem, and a sensor-based stacking task requiring replanning. These demonstrate robust execution of long sequences of sensor-based manipulation tasks, which makes the resulting platform a solid foundation for researchers in task-and-motion planning, educators, and quick prototyping of household, industrial and warehouse automation tasks.

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References (25)
  1. Soft robotics. IEEE Robotics & Automation Magazine, 15(3):20–30, 2008.
  2. Learning dexterous in-hand manipulation. The International Journal of Robotics Research, 39(1):3–20, 2020.
  3. Benchmarking protocol for grasp planning algorithms. IEEE Robotics and Automation Letters, 5(2):315–322, 2019.
  4. Surprisingly robust in-hand manipulation: An empirical study. arXiv preprint arXiv:2201.11503, 2022.
  5. Advanced grasping with the pisa/iit softhand. In Robotic Grasping and Manipulation: First Robotic Grasping and Manipulation Challenge, RGMC 2016, Held in Conjunction with IROS 2016, Daejeon, South Korea, October 10–12, 2016, Revised Papers 1, pages 19–38. Springer, 2018.
  6. Yale-cmu-berkeley dataset for robotic manipulation research. The International Journal of Robotics Research, 36(3):261–268, 2017.
  7. Adaptive synergies for the design and control of the pisa/iit softhand. The International Journal of Robotics Research, 33(5):768–782, 2014.
  8. M. Colledanchise and P. Ögren. Behavior trees in robotics and AI: An introduction. CRC Press, 2018.
  9. P. Corke and J. Haviland. Not your grandmother’s toolbox–the robotics toolbox reinvented for python. In 2021 IEEE International Conference on Robotics and Automation (ICRA), pages 11357–11363. IEEE, 2021.
  10. Analysis and observations from the first amazon picking challenge. IEEE Transactions on Automation Science and Engineering, 15(1):172–188, 2016.
  11. Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms. Mit Press, 2022.
  12. Systems, devices, components, and methods for a compact robotic gripper with palm-mounted sensing, grasping, and computing devices and components, Oct. 19 2021. US Patent 11,148,295.
  13. The elliott and connolly benchmark: A test for evaluating the in-hand dexterity of robot hands. In 2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids), pages 238–245. IEEE, 2021.
  14. R. S. Fearing. Simplified grasping and manipulation with dextrous robot hands. IEEE Journal on Robotics and Automation, 2(4):188–195, 1986.
  15. M. Fox and D. Long. Pddl2.1: An extension to pddl for expressing temporal planning domains. Journal of artificial intelligence research, 20:61–124, 2003.
  16. Benchmarking bimanual cloth manipulation. IEEE Robotics and Automation Letters, 5(2):1111–1118, 2020.
  17. M. Helmert. The fast downward planning system. Journal of Artificial Intelligence Research, 26:191–246, 2006.
  18. R. Karem. py2pddl. https://github.com/remykarem/py2pddl, 2022.
  19. Benchmarking cluttered robot pick-and-place manipulation with the box and blocks test. IEEE Robotics and Automation Letters, 5(2):454–461, 2019.
  20. Manipulation using the “utah” prosthetic hand: The role of stiffness in manipulation. In Robotic Grasping and Manipulation: First Robotic Grasping and Manipulation Challenge, RGMC 2016, Held in Conjunction with IROS 2016, Daejeon, South Korea, October 10–12, 2016, Revised Papers 1, pages 107–116. Springer, 2018.
  21. Mobile manipulation hackathon: Moving into real world applications. IEEE Robotics & Automation Magazine, 28(2):112–124, 2021.
  22. Robotic grasping and manipulation competition: task pool. In Robotic Grasping and Manipulation: First Robotic Grasping and Manipulation Challenge, RGMC 2016, Held in Conjunction with IROS 2016, Daejeon, South Korea, October 10–12, 2016, Revised Papers 1, pages 1–18. Springer, 2018.
  23. A practical approach to insertion with variable socket position using deep reinforcement learning. In 2019 international conference on robotics and automation (ICRA), pages 754–760. IEEE, 2019.
  24. Robots assembling machines: learning from the world robot summit 2018 assembly challenge. Advanced Robotics, 34(7-8):408–421, 2020.
  25. Autonomous industrial assembly using force, torque, and rgb-d sensing. Advanced Robotics, 34(7-8):546–559, 2020.
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Authors (4)
  1. Nikolaus Correll (31 papers)
  2. Dylan Kriegman (2 papers)
  3. Stephen Otto (1 paper)
  4. James Watson (9 papers)
Citations (5)
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