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Human-embodied drone interface for aerial manipulation: advantages and challenges

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Abstract

Drones have performed various tasks, such as surveillance, photography, agriculture, and package delivery. However, these tasks typically involve drones simply observing or capturing information from their surroundings without physically interacting with them. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply touching it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drilling into surfaces, and sealing cracks via a drone. For over a decade, researchers have been working on aerial manipulation for industrial applications. These works are valuable to aerial manipulation but have not been widespread in the public domain yet. This is because most of the works are conducted in controlled indoor environments (e.g., motion capture systems), and the knowledge gap exists between researchers and the wider public who are interested in deploying aerial manipulation for practical tasks. To fill this gap, our recent work integrated the worker’s experience into aerial manipulation using haptic technology. The net effect is that such a human-in-the-loop system could enable workers to leverage their experience to complete manipulation tasks while remotely controlling a mobile manipulating drone on the task site. The system increased the feasibility and adaptiveness of aerial manipulation. The remaining challenges are completing tasks beyond the operator’s line-of-sight and lack of dexterity. To address the challenges, we present a human-embodied drone interface in this article. The interface consists of immersive virtual/augmented reality and haptic technologies. Such an interface allows the drones to embody and transport the operator’s senses, actions, and presence to a remote location in real-time. Therefore, the operator can both physically interact with the environment and socially interact with actual workers on the worksite. Two different human-embodied interfaces are developed and tested with several tasks suggested by the United States Department-of-Transportation: pick-and-place, drilling, peg-in-hole, and key insert/rotation. The conclusion describes the advantages and challenges of the interface with future works.

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References

  1. Ollero A, Tognon M, Suarez A, Lee D, Franchi A (2021) Past present and future of aerial robotic manipulators. IEEE Trans Robot 38(1):626–645

    Article  Google Scholar 

  2. Ruggiero F, Lippiello V, Ollero A (2018) Aerial manipulation: a literature review. IEEE Robot Autom Lett 3(3):1957–1964

    Article  Google Scholar 

  3. Orsag M, Korpela C, Oh PY, Bogdan S (2018) Aerial manipulation. Springer Publishing

    Book  Google Scholar 

  4. Orsag M, Korpela C, Bogdan S, Oh P (2017) Dexterous aerial robots - mobile manipulation using unmanned aerial systems. IEEE Trans Robot 33(6):1453–1466

    Article  Google Scholar 

  5. Garimella G, Sheckells M, Kim S, Baraban G, Kobilarov M (2021) Improving the reliability of pick-and-place with aerial vehicles through fault-tolerant software and a custom magnetic end-effector. IEEE Robot Autom Lett 6(4):7501–7508

    Article  Google Scholar 

  6. Chermprayong P, Zhang K, Xiao F, Kovac M (2019) An integrated delta manipulator for aerial repair: a new aerial robotic system. IEEE Robot Autom Mag 26(1):54–66

    Article  Google Scholar 

  7. Shi F, Zhao M, Murooka M, Okada K, Inaba M (2020) Aerial regrasping: pivoting with transformable multilink aerial robot. In: 2020 IEEE international conference on robotics and automation (ICRA), pp 200-207

  8. Suarez A, Salmoral R, Zarco-Periñan PJ, Ollero A (2021) Experimental evaluation of aerial manipulation robot in contact with 15 kV power line: shielded and long reach configurations. IEEE Access 9:94573–94585

    Article  Google Scholar 

  9. Bodie K, Tognon M, Siegwart R (2021) Dynamic end effector tracking with an omnidirectional parallel aerial manipulator. IEEE Robot Autom Lett 6(4):8165–8172

    Article  Google Scholar 

  10. Orr L, Stephens B, Kocer BB, Kovac M (2021) A high payload aerial platform for infrastructure repair and manufacturing, 2021 aerial robotic systems physically interacting with the environment (AIRPHARO). Biograd na Moru, Croatia, pp 1–6

    Google Scholar 

  11. Ding C, Lu L (2021) A tilting-rotor unmanned aerial vehicle for enhanced aerial locomotion and manipulation capabilities: design, control, and applications. IEEE/ASME Trans Mechatron 26(4):2237–2248

    Article  Google Scholar 

  12. Sugito N, Zhao M, Anzai T, Nishio T, Okada K, Inaba M (2022) Aerial manipulation using contact with the environment by thrust vectorable multilinked aerial robot. In: 2022 international conference on robotics and automation (ICRA), Philadelphia, PA, USA, pp 54-60

  13. Schuster M, Bernstein D, Reck P, Hamaza S, Beitelschmidt M (2022) Automated aerial screwing with a fully actuated aerial manipulator. In: 2022 IEEE/RSJ international conference on intelligent robots and systems (IROS), Kyoto, Japan, pp 3340–3347

  14. Mohammadi M, Franchi A, Barcelli D, Prattichizzo D (2016) Cooperative aerial tele-manipulation with haptic feedback. In: IEEE international conference on intelligent robots and systems (IROS), pp 5092–5098

  15. Mohammadi M, Franchi A, Barcelli D, Prattichizzo D (2016) Cooperative aerial tele-manipulation with haptic feedback. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 5092–5098

  16. Park S et al (2018) ODAR: aerial manipulation platform enabling omnidirectional wrench generation. IEEE/ASME Trans Mechatron 23(4):1907–1918

    Article  Google Scholar 

  17. Kim D, Oh PY (2020 ) Testing-and-evaluation platform for haptic-based aerial manipulation with drones. IEEE american control conference, pp 1453–1458

  18. Kim D, Oh PY (2020) Human-drone interaction for aerially manipulated drilling using haptic feedback. In: IEEE international conference on intelligent robots and systems (IROS)

  19. ANA Avatar Xprize [Online] Available: https://avatar.xprize.org/prizes/avatar

  20. Yashin GA, Trinitatova D, Agishev RT, Ibrahimov R, Tsetserukou D (2019) AeroVr: virtual reality-based teleoperation with tactile feedback for aerial manipulation. In: IEEE international conference on advanced robotics (ICAR), pp 767–772

  21. Lee J, et al (2020) Visual-inertial telepresence for aerial manipulation. In: IEEE international conference on robotics and automation (ICRA)

  22. Jauregui DAG, Argelaguet F, Olivier A, Marchal M, Multon F, Lecuyer A (2014) Toward “pseudo-haptic avatars": modifying the visual animation of self-avatar can simulate the perception of weight lifting. IEEE Trans Vis Comput Graph 20(4):654–661

    Article  Google Scholar 

  23. Walker ME, Szafir D, Rae I (2019) The influence of size in augmented reality telepresence avatars. In: IEEE conference on virtual reality and 3D user interfaces (VR), pp 538–546

  24. Takala TM, Hsin CC, Kawai T (2019) Stand-alone, wearable system for full body vr avatars: towards physics-based 3D interaction. In: IEEE conference on virtual reality and 3D user interfaces (VR), pp 1398–1398

  25. Orsag M, Korpela C, Bogdan S, Oh P (2014) Valve turning using a dual-arm aerial manipulator. In: International conference on unmanned aircraft systems (ICUAS), pp 836–841

  26. Chiaverini S, Siciliano B, Egeland O (1994) Review of the damped least-squares inverse kinematics with experiments on an industrial robot manipulator. IEEE Trans Control Syst Technol 2(2):123–134

    Article  Google Scholar 

  27. Orocos Kinematics and Dynamics [Online] Available : https://www.orocos.org/kdl.html

  28. Dynamixel MX-28 E-Manual [Online] Available: http://emanual.robotis.com/docs/en/dxl/mx/mx-28/

  29. Oh PY, Sohn K, Jang G, Jun Y, Cho BK (2017) Technical overview of team DRC-Hubo@ UNLV’s approach to the 2015 DARPA robotics challenge finals. J Field Robot 34(5):874–896

    Article  Google Scholar 

  30. ROS Sharp (ROS\(\#\)) [Online] Available: https://github.com/siemens/ros-sharp

  31. Ruggiero F, Lippiello V, Ollero A (2018) Aerial manipulation: a literature review. IEEE Robot Autom Lett 3(3):1957–1964

    Article  Google Scholar 

  32. Lee D, Seo H, Jang I, Lee SJ, Kim HJ (2021) Aerial manipulator pushing a movable structure using a DOB-based robust controller. IEEE Robot Autom Lett 6(2):723–730

    Article  Google Scholar 

  33. Shim H, Park G, Joo Y et al (2016) Yet another tutorial of disturbance observer: robust stabilization and recovery of nominal performance. Control Theory Technol 14:237–249

    Article  MathSciNet  Google Scholar 

  34. Lee SJ, Kim S, Johansson KH, Kim HJ (2016) Robust acceleration control of a hexarotor UAV with a disturbance observer. In: IEEE 55th conference on decision and control (CDC), pp 4166–4171

  35. Microsoft Mixed Reality Toolkit(MRTK) [Online] Available: https://docs.microsoft.com/en-us/windows/mixed-reality/develop/unity/mrtk-getting-started

  36. Kim, D (2021) A human-embodied drone for dexterous aerial manipulation. UNLV Theses, Dissertations, Professional Papers, and Capstones, p 4298

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Acknowledgements

This article is based primarily on the author’s dissertation work in [36]

Funding

Financial support for this study is provided by the U.S. Department of Transportation, Office of the Assistant Secretary for Research and Technology (USDOT/OST-R) under Grant No. 69A3551747126 through the INSPIRE University Transportation Center (http://inspire-utc.mst.edu) at Missouri University of Science and Technology. The views, opinions, findings and conclusions reflected in this publication are solely those of the author and do not represent the official policy or position of the USDOT/OST-R, or any State or other entity.

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Correspondence to Dongbin Kim.

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Kim, D., Oh, P.Y. Human-embodied drone interface for aerial manipulation: advantages and challenges. Intel Serv Robotics (2024). https://doi.org/10.1007/s11370-024-00535-4

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