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Pushing in the Dark: A Reactive Pushing Strategy for Mobile Robots Using Tactile Feedback (2403.09305v1)

Published 14 Mar 2024 in cs.RO

Abstract: For mobile robots, navigating cluttered or dynamic environments often necessitates non-prehensile manipulation, particularly when faced with objects that are too large, irregular, or fragile to grasp. The unpredictable behavior and varying physical properties of these objects significantly complicate manipulation tasks. To address this challenge, this manuscript proposes a novel Reactive Pushing Strategy. This strategy allows a mobile robot to dynamically adjust its base movements in real-time to achieve successful pushing maneuvers towards a target location. Notably, our strategy adapts the robot motion based on changes in contact location obtained through the tactile sensor covering the base, avoiding dependence on object-related assumptions and its modeled behavior. The effectiveness of the Reactive Pushing Strategy was initially evaluated in the simulation environment, where it significantly outperformed the compared baseline approaches. Following this, we validated the proposed strategy through real-world experiments, demonstrating the robot capability to push objects to the target points located in the entire vicinity of the robot. In both simulation and real-world experiments, the object-specific properties (shape, mass, friction, inertia) were altered along with the changes in target locations to assess the robustness of the proposed method comprehensively.

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References (26)
  1. F. Ruggiero, V. Lippiello, and B. Siciliano, “Nonprehensile dynamic manipulation: A survey,” IEEE Robotics and Automation Letters, vol. 3, no. 3, pp. 1711–1718, 2018.
  2. M. Wang, R. Luo, A. O. Önol, and T. Padir, “Affordance-based mobile robot navigation among movable obstacles,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE Press, 2020, p. 2734–2740.
  3. Y. Tang, H. Zhu, S. Potters, M. Wisse, and W. Pan, “Unwieldy object delivery with nonholonomic mobile base: A stable pushing approach,” IEEE Robotics and Automation Letters, vol. 8, no. 11, pp. 7727–7734, 2023.
  4. K. Ellis, D. Hadjivelichkov, V. Modugno, D. Stoyanov, and D. Kanoulas, “Navigation among movable obstacles via multi-object pushing into storage zones,” IEEE Access, vol. 11, pp. 3174–3183, 2023.
  5. J. Stüber, C. Zito, and R. Stolkin, “Let’s push things forward: A survey on robot pushing,” Frontiers in Robotics and AI, vol. 7, 2019.
  6. S. Goyal, A. Ruina, and J. Papadopoulos, “Planar sliding with dry friction part 1. limit surface and moment function,” Wear, vol. 143, no. 2, pp. 307–330, 1991.
  7. K. M. Lynch and M. T. Mason, “Stable pushing: Mechanics, controllability, and planning,” The International Journal of Robotics Research, vol. 15, no. 6, pp. 533–556, 1996.
  8. J. Zhou, Y. Hou, and M. T. Mason, “Pushing revisited: Differential flatness, trajectory planning, and stabilization,” The International Journal of Robotics Research, vol. 38, no. 12-13, pp. 1477–1489, 2019.
  9. F. Bertoncelli, F. Ruggiero, and L. Sabattini, “Linear time-varying mpc for nonprehensile object manipulation with a nonholonomic mobile robot,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020, pp. 11 032–11 038.
  10. F. R. Hogan and A. Rodriguez, “Reactive planar non-prehensile manipulation with hybrid model predictive control,” The International Journal of Robotics Research, vol. 39, pp. 755 – 773, 2020.
  11. F. R. Hogan, E. R. Grau, and A. Rodriguez, “Reactive planar manipulation with convex hybrid mpc,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 247–253.
  12. K. M. Lynch, H. Maekawa, and K. Tanie, “Manipulation and active sensing by pushing using tactile feedback,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1, pp. 416–421, 1992.
  13. M. Lau, J. Mitani, and T. Igarashi, “Automatic learning of pushing strategy for delivery of irregular-shaped objects,” in 2011 IEEE International Conference on Robotics and Automation, 2011, pp. 3733–3738.
  14. F. Ruiz-Ugalde, G. Cheng, and M. Beetz, “Prediction of action outcomes using an object model,” in 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010, pp. 1708–1713.
  15. ——, “Fast adaptation for effect-aware pushing,” in 2011 11th IEEE-RAS International Conference on Humanoid Robots, 2011, pp. 614–621.
  16. T. Hermans, F. Li, J. M. Rehg, and A. F. Bobick, “Learning contact locations for pushing and orienting unknown objects,” in 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2013, pp. 435–442.
  17. T. Mericli, M. Veloso, and H. L. Akin, “Achievable push-manipulation for complex passive mobile objects using past experience,” vol. 1, 2013, pp. 71–78.
  18. T. Meriçli, M. M. Veloso, and H. L. Akin, “Push-manipulation of complex passive mobile objects using experimentally acquired motion models,” Autonomous Robots, vol. 38, pp. 317–329, 2015.
  19. P. Agrawal, A. Nair, P. Abbeel, J. Malik, and S. Levine, “Learning to poke by poking: Experiential learning of intuitive physics,” 06 2016, p. 5092–5100.
  20. T. Igarashi, Y. Kamiyama, and M. Inami, “A dipole field for object delivery by pushing on a flat surface,” 2010 IEEE International Conference on Robotics and Automation, pp. 5114–5119, 2010.
  21. S. Krivic, E. Ugur, and J. Piater, “A robust pushing skill for object delivery between obstacles,” in 2016 IEEE International Conference on Automation Science and Engineering (CASE), 2016, pp. 1184–1189.
  22. S. Krivić and J. Piater, “Pushing corridors for delivering unknown objects with a mobile robot,” Autonomous Robots, vol. 43, pp. 1435–1452, 2019.
  23. M. Leonori, J. M. Gandarias, and A. Ajoudani, “Moca-s: A sensitive mobile collaborative robotic assistant exploiting low-cost capacitive tactile cover and whole-body control,” IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7920–7927, 2022.
  24. R. Arbaud, M. Najafi, J. M. Gandarias, M. Lorenzini, U. C. Paul, A. Zych, A. Athanassiou, P. Cataldi, and A. Ajoudani, “Toward sustainable haptics: A wearable vibrotactile solar-powered system with biodegradable components,” Advanced Materials Technologies, vol. 9, no. 5, p. 2301265, 2024.
  25. J. Xie and N. Chakraborty, “Rigid body dynamic simulation with line and surface contact,” in 2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), 2016, pp. 9–15.
  26. http://classic.gazebosim.org/tutorials?tut=contact_sensor.
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Authors (4)
  1. Idil Ozdamar (8 papers)
  2. Doganay Sirintuna (8 papers)
  3. Robin Arbaud (3 papers)
  4. Arash Ajoudani (63 papers)

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