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A Modular Pneumatic Soft Gripper Design for Aerial Grasping and Landing (2311.00390v3)

Published 1 Nov 2023 in cs.RO

Abstract: Aerial robots have garnered significant attention due to their potential applications in various industries, such as inspection, search and rescue, and drone delivery. Successful missions often depend on the ability of these robots to grasp and land effectively. This paper presents a novel modular soft gripper design tailored explicitly for aerial grasping and landing operations. The proposed modular pneumatic soft gripper incorporates a feed-forward proportional controller to regulate pressure, enabling compliant gripping capabilities. The modular connectors of the soft fingers offer two configurations for the 4-tip soft gripper, H-base (cylindrical) and X-base (spherical), allowing adaptability to different target objects. Additionally, the gripper can serve as a soft landing gear when deflated, eliminating the need for an extra landing gear. This design reduces weight, simplifies aerial manipulation control, and enhances flight efficiency. We demonstrate the efficacy of indoor aerial grasping and achieve a maximum payload of 217 g using the proposed soft aerial vehicle and its H-base pneumatic soft gripper (808 g).

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References (23)
  1. J. Meng, J. Buzzatto, Y. Liu, and M. Liarokapis, “On aerial robots with grasping and perching capabilities: A comprehensive review,” Frontiers in Robotics and AI, vol. 8, p. 739173, 2022.
  2. G. Muchiri and S. Kimathi, “A review of applications and potential applications of uav,” in Proceedings of the Sustainable Research and Innovation Conference, 2022, pp. 280–283.
  3. S. Yeong, L. King, and S. Dol, “A review on marine search and rescue operations using unmanned aerial vehicles,” International Journal of Marine and Environmental Sciences, vol. 9, no. 2, pp. 396–399, 2015.
  4. J. Qi, J. Kang, and X. Lu, “Design and research of uav autonomous grasping system,” in 2017 IEEE International Conference on Unmanned Systems (ICUS).   IEEE, 2017, pp. 126–131.
  5. C. A. Thiels, J. M. Aho, S. P. Zietlow, and D. H. Jenkins, “Use of unmanned aerial vehicles for medical product transport,” Air medical journal, vol. 34, no. 2, pp. 104–108, 2015.
  6. J. Fishman, S. Ubellacker, N. Hughes, and L. Carlone, “Dynamic grasping with a” soft” drone: From theory to practice,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2021, pp. 4214–4221.
  7. Y. Zhu, X. He, P. Zhang, G. Guo, and X. Zhang, “Perching and grasping mechanism inspired by a bird’s claw,” Machines, vol. 10, no. 8, p. 656, 2022.
  8. D. Rus and M. T. Tolley, “Design, fabrication and control of soft robots,” Nature, vol. 521, no. 7553, pp. 467–475, 2015.
  9. J. P. King, D. Bauer, C. Schlagenhauf, K.-H. Chang, D. Moro, N. Pollard, and S. Coros, “Design. fabrication, and evaluation of tendon-driven multi-fingered foam hands,” in 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids).   IEEE, 2018, pp. 1–9.
  10. M. Manti, T. Hassan, G. Passetti, N. D’Elia, C. Laschi, and M. Cianchetti, “A bioinspired soft robotic gripper for adaptable and effective grasping,” Soft Robotics, vol. 2, no. 3, pp. 107–116, 2015.
  11. T. Hassan, M. Manti, G. Passetti, N. d’Elia, M. Cianchetti, and C. Laschi, “Design and development of a bio-inspired, under-actuated soft gripper,” in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).   IEEE, 2015, pp. 3619–3622.
  12. P. Ramon-Soria, A. E. Gomez-Tamm, F. J. Garcia-Rubiales, B. C. Arrue, and A. Ollero, “Autonomous landing on pipes using soft gripper for inspection and maintenance in outdoor environments,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2019, pp. 5832–5839.
  13. J. Fishman and L. Carlone, “Control and trajectory optimization for soft aerial manipulation,” in 2021 IEEE Aerospace Conference (50100).   IEEE, 2021, pp. 1–17.
  14. R. Peng, Z. Wang, and P. Lu, “Aecom: An aerial continuum manipulator with precise kinematic modeling for variable loading and tendon-slacking prevention,” arXiv preprint arXiv:2110.14180, 2021.
  15. J. L. Chien, C. Leong, J. Liu, and S. Foong, “Design and control of an aerial-ground tethered tendon-driven continuum robot with hybrid routing,” Robotics and Autonomous Systems, vol. 161, p. 104344, 2023.
  16. T. S. Y. Min, L. Y. Lee, and S. G. Nurzaman, “Bayesian optimization of pneumatic soft grippers via reconfigurable modular molds,” in 2023 IEEE International Conference on Soft Robotics (RoboSoft).   IEEE, 2023, pp. 1–6.
  17. A. Shtarbanov, “Flowio development platform–the pneumatic “raspberry pi” for soft robotics,” in Extended abstracts of the 2021 CHI conference on human factors in computing systems, 2021, pp. 1–6.
  18. J. T. Ping, B. H. Khoo, O. A. Syadiqeen, N. Khoo, C. P. Tan, and S. G. Nurzaman, “Aerial grasping by a quadrotor uav with a soft material gripper.”
  19. D. Sarkar, A. Arora, S. Sen, S. S. Katta, D. Shashank, M. Rohan, and S. Saha, “Development of an autonomous uav integrated with a manipulator and a soft gripper,” in 2022 13th Asian Control Conference (ASCC).   IEEE, 2022, pp. 2212–2217.
  20. C. Tawk, R. Mutlu, and G. Alici, “A 3d printed modular soft gripper integrated with metamaterials for conformal grasping,” Frontiers in Robotics and AI, vol. 8, p. 799230, 2022.
  21. J. Zhang, A. Jackson, N. Mentzer, and R. Kramer, “A modular, reconfigurable mold for a soft robotic gripper design activity,” Frontiers in Robotics and AI, vol. 4, p. 46, 2017.
  22. B. Jiang, B. Li, W. Zhou, L.-Y. Lo, C.-K. Chen, and C.-Y. Wen, “Neural network based model predictive control for a quadrotor uav,” Aerospace, vol. 9, no. 8, p. 460, 2022.
  23. B. Li, W. Zhou, J. Sun, C.-Y. Wen, and C.-K. Chen, “Development of model predictive controller for a tail-sitter vtol uav in hover flight,” Sensors, vol. 18, no. 9, p. 2859, 2018.
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