skip to main content
10.1145/3526113.3545674acmconferencesArticle/Chapter ViewAbstractPublication PagesuistConference Proceedingsconference-collections
research-article

Computational Design of Active Kinesthetic Garments

Authors Info & Claims
Published:28 October 2022Publication History

ABSTRACT

Garments with the ability to provide kinesthetic force-feedback on-demand can augment human capabilities in a non-obtrusive way, enabling numerous applications in VR haptics, motion assistance, and robotic control. However, designing such garments is a complex, and often manual task, particularly when the goal is to resist multiple motions with a single design. In this work, we propose a computational pipeline for designing connecting structures between active components—one of the central challenges in this context. We focus on electrostatic (ES) clutches that are compliant in their passive state while strongly resisting elongation when activated. Our method automatically computes optimized connecting structures that efficiently resist a range of pre-defined body motions on demand. We propose a novel dual-objective optimization approach to simultaneously maximize the resistance to motion when clutches are active, while minimizing resistance when inactive. We demonstrate our method on a set of problems involving different body sites and a range of motions. We further fabricate and evaluate a subset of our automatically created designs against manually created baselines using mechanical testing and in a VR pointing study.

Skip Supplemental Material Section

Supplemental Material

active_kinesthetic_garments.mp4

mp4

255.1 MB

References

  1. 2020. High Force Density Textile Electrostatic Clutch. Advanced Materials Technologies 5, 4 (apr 2020), 1900895. https://doi.org/10.1002/admt.201900895Google ScholarGoogle Scholar
  2. Hassanin Al-Fahaam, Steve Davis, and Samia Nefti-Meziani. 2016. Wrist rehabilitation exoskeleton robot based on pneumatic soft actuators. In 2016 International Conference for Students on Applied Engineering (ICSAE). IEEE, 491–496.Google ScholarGoogle ScholarCross RefCross Ref
  3. Ahmed Al Maimani and Anne Roudaut. 2017. Frozen suit: designing a changeable stiffness suit and its application to haptic games. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 2440–2448.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Alan T. Asbeck, Stefano M.M. De Rossi, Ignacio Galiana, Ye Ding, and Conor J. Walsh. 2014. Stronger, smarter, softer: Next-generation wearable robots. IEEE Robotics and Automation Magazine 21, 4 (2014), 22–33. https://doi.org/10.1109/MRA.2014.2360283Google ScholarGoogle ScholarCross RefCross Ref
  5. Gareth Barnaby and Anne Roudaut. 2019. Mantis: A Scalable, Lightweight and Accessible Architecture to Build Multiform Force Feedback Systems. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology. ACM, New York, NY, USA, 937–948. https://doi.org/10.1145/3332165.3347909Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Martin Philip Bendsoe and Ole Sigmund. 2013. Topology optimization: theory, methods, and applications. Springer Science & Business Media.Google ScholarGoogle Scholar
  7. Javier Bonet and Richard D. Wood. 2008. Nonlinear Continuum Mechanics for Finite Element Analysis (2 ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511755446Google ScholarGoogle Scholar
  8. Tyler E Bruns and Daniel A Tortorelli. 2001. Topology optimization of non-linear elastic structures and compliant mechanisms. Computer methods in applied mechanics and engineering 190, 26-27(2001), 3443–3459.Google ScholarGoogle Scholar
  9. Bing Chen, Hao Ma, Lai-Yin Qin, Fei Gao, Kai-Ming Chan, Sheung-Wai Law, Ling Qin, and Wei-Hsin Liao. 2016. Recent developments and challenges of lower extremity exoskeletons. Journal of Orthopaedic Translation 5 (apr 2016), 26–37. https://doi.org/10.1016/j.jot.2015.09.007Google ScholarGoogle Scholar
  10. Inrak Choi, Nick Corson, Lizzie Peiros, Elliot W. Hawkes, Sean Keller, and Sean Follmer. 2018. A Soft, Controllable, High Force Density Linear Brake Utilizing Layer Jamming. IEEE Robotics and Automation Letters 3, 1 (jan 2018), 450–457. https://doi.org/10.1109/LRA.2017.2761938Google ScholarGoogle ScholarCross RefCross Ref
  11. Alexandra Delazio, Ken Nakagaki, Jill Fain Lehman, Roberta L. Klatzky, Alanson P. Sample, and Scott E. Hudson. 2018. Force jacket: Pneumatically-actuated jacket for embodied haptic experiences. In Conference on Human Factors in Computing Systems - Proceedings, Vol. 2018-April. ACM, New York, NY, USA, 1–12. https://doi.org/10.1145/3173574.3173894Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Stuart Diller, Carmel Majidi, and Steven H. Collins. 2016. A lightweight, low-power electroadhesive clutch and spring for exoskeleton actuation. In 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 682–689. https://doi.org/10.1109/ICRA.2016.7487194Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Cathy Fang, Yang Zhang, Matthew Dworman, and Chris Harrison. 2020. Wireality: Enabling Complex Tangible Geometries in Virtual Reality with Worn Multi-String Haptics. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 1–10. https://doi.org/10.1145/3313831.3376470Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Mohsen Gholami, Ahmad Rezaei, Tyler J Cuthbert, Christopher Napier, and Carlo Menon. 2019. Lower body kinematics monitoring in running using fabric-based wearable sensors and deep convolutional neural networks. Sensors 19, 23 (2019), 5325.Google ScholarGoogle ScholarCross RefCross Ref
  15. Sebastian Günther, Mohit Makhija, Florian Müller, Dominik Schön, Max Mühlhäuser, and Markus Funk. 2019. PneumAct: Pneumatic Kinesthetic Actuation of Body Joints in Virtual Reality Environments. In Proceedings of the 2019 on Designing Interactive Systems Conference. ACM, 227–240.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Ronan Hinchet and Herbert Shea. 2019. High Force Density Textile Electrostatic Clutch. Advanced Materials Technologies(2019), 1900895. https://doi.org/10.1002/admt.201900895 arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/admt.201900895Google ScholarGoogle Scholar
  17. Ronan Hinchet, Velko Vechev, Herbert Shea, and Otmar Hilliges. 2018. Dextres: Wearable haptic feedback for grasping in vr via a thin form-factor electrostatic brake. In Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology. 901–912.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Xiaodong Huang and YM Xie. 2007. Convergent and mesh-independent solutions for the bi-directional evolutionary structural optimization method. Finite elements in analysis and design 43, 14 (2007), 1039–1049.Google ScholarGoogle Scholar
  19. Xiaodong Huang and Yi Min Xie. 2009. Bi-directional evolutionary topology optimization of continuum structures with one or multiple materials. Computational Mechanics 43, 3 (2009), 393–401.Google ScholarGoogle ScholarCross RefCross Ref
  20. Jinsoo Kim, Giuk Lee, Roman Heimgartner, Dheepak Arumukhom Revi, Nikos Karavas, Danielle Nathanson, Ignacio Galiana, Asa Eckert-Erdheim, Patrick Murphy, David Perry, 2019. Reducing the metabolic rate of walking and running with a versatile, portable exosuit. Science 365, 6454 (2019), 668–672.Google ScholarGoogle Scholar
  21. Sangjun Lee, Nikos Karavas, Brenna T Quinlivan, Danielle LouiseRyan, David Perry, Asa Eckert-Erdheim, Patrick Murphy, Taylor Greenberg Goldy, Nicolas Menard, Maria Athanassiu, 2018. Autonomous multi-joint soft exosuit for assistance with walking overground. In 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2812–2819.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Dong C Liu and Jorge Nocedal. 1989. On the limited memory BFGS method for large scale optimization. Mathematical programming 45, 1 (1989), 503–528.Google ScholarGoogle Scholar
  23. Zishun Liu, Xingjian Han, Yuchen Zhang, Xiangjia Chen, Yu-Kun Lai, Eugeni L Doubrovski, Emily Whiting, and Charlie CL Wang. 2021. Knitting 4D garments with elasticity controlled for body motion. ACM Transactions on Graphics (TOG) 40, 4 (2021), 1–16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J Black. 2015. SMPL: A skinned multi-person linear model. ACM transactions on graphics (TOG) 34, 6 (2015), 248.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Naureen Mahmood, Nima Ghorbani, Nikolaus F Troje, Gerard Pons-Moll, and Michael J Black. 2019. AMASS: Archive of motion capture as surface shapes. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 5442–5451.Google ScholarGoogle ScholarCross RefCross Ref
  26. Jonàs Martínez, Jérémie Dumas, Sylvain Lefebvre, and Li-Yi Wei. 2015. Structure and appearance optimization for controllable shape design. ACM Transactions on Graphics (TOG) 34, 6 (2015), 1–11.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Juan Montes, Bernhard Thomaszewski, Sudhir Mudur, and Tiberiu Popa. 2020. Computational design of skintight clothing. ACM Transactions on Graphics (TOG) 39, 4 (2020), 105–1.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sachith Muthukumarana, Moritz Alexander Messerschmidt, Denys JC Matthies, Jürgen Steimle, Philipp M Scholl, and Suranga Nanayakkara. 2021. Clothtiles: A prototyping platform to fabricate customized actuators on clothing using 3d printing and shape-memory alloys. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–12.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Jesús Ortiz, Tommaso Poliero, Giovanni Cairoli, Eveline Graf, and Darwin G Caldwell. 2017. Energy efficiency analysis and design optimization of an actuation system in a soft modular lower limb exoskeleton. IEEE Robotics and Automation Letters 3, 1 (2017), 484–491.Google ScholarGoogle ScholarCross RefCross Ref
  30. Ahmed AA Osman, Timo Bolkart, and Michael J Black. 2020. Star: Sparse trained articulated human body regressor. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part VI 16. Springer, 598–613.Google ScholarGoogle Scholar
  31. A Cengiz Öztireli, Gael Guennebaud, and Markus Gross. 2009. Feature preserving point set surfaces based on non-linear kernel regression. In Computer graphics forum, Vol. 28. Wiley Online Library, 493–501.Google ScholarGoogle Scholar
  32. Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32. Curran Associates, Inc., 8024–8035. http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdfGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  33. Vivek Ramachandran, Matteo Macchini, and Dario Floreano. 2021. Arm-wrist haptic sleeve for drone teleoperation. IEEE Robotics and Automation Letters(2021).Google ScholarGoogle Scholar
  34. Vivek Ramachandran, Fabian Schilling, Amy R. Wu, and Dario Floreano. 2021. Smart Textiles that Teach: Fabric‐Based Haptic Device Improves the Rate of Motor Learning. Advanced Intelligent Systems 3, 11 (nov 2021), 2100043. https://doi.org/10.1002/aisy.202100043 arxiv:2106.06332Google ScholarGoogle ScholarCross RefCross Ref
  35. Carine Rognon, Stefano Mintchev, Fabio Dell’Agnola, Alexandre Cherpillod, David Atienza, and Dario Floreano. 2018. Flyjacket: An upper body soft exoskeleton for immersive drone control. IEEE Robotics and Automation Letters 3, 3 (2018), 2362–2369.Google ScholarGoogle ScholarCross RefCross Ref
  36. Vanessa Sanchez, Conor J Walsh, and Robert J Wood. 2021. Textile technology for soft robotic and autonomous garments. Advanced Functional Materials 31, 6 (2021), 2008278.Google ScholarGoogle ScholarCross RefCross Ref
  37. A. Schiele and Gerd Hirzinger. 2011. A new generation of ergonomic exoskeletons - the high-performance X-Arm-2 for Space Robotics Telepresence. In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2158–2165. https://doi.org/10.1109/IROS.2011.6048553Google ScholarGoogle ScholarCross RefCross Ref
  38. Christian Schumacher, Bernhard Thomaszewski, and Markus Gross. 2016. Stenciling: Designing Structurally-Sound Surfaces with Decorative Patterns. In Computer Graphics Forum, Vol. 35. Wiley Online Library, 101–110.Google ScholarGoogle Scholar
  39. Yang Shen, Peter Walker Ferguson, and Jacob Rosen. 2019. Upper limb exoskeleton systems-overview. In Wearable Robotics: Systems and Applications. Elsevier, 1–22. https://doi.org/10.1016/B978-0-12-814659-0.00001-1Google ScholarGoogle Scholar
  40. Mélina Skouras, Bernhard Thomaszewski, Stelian Coros, Bernd Bickel, and Markus Gross. 2013. Computational Design of Actuated Deformable Characters. ACM Trans. Graph. 32, 4, Article 82 (July 2013), 10 pages. https://doi.org/10.1145/2461912.2461979Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Velko Vechev, Juan Zarate, Bernhard Thomaszewski, and Otmar Hilliges. 2022. Computational Design of Kinesthetic Garments. In Computer Graphics Forum, Vol. 40. Wiley Online Library, 101–110.Google ScholarGoogle Scholar
  42. Jonas Zehnder, Yue Li, Stelian Coros, and Bernhard Thomaszewski. 2021. NTopo: Mesh-free Topology Optimization using Implicit Neural Representations. Advances in Neural Information Processing Systems 34 (2021).Google ScholarGoogle Scholar
  43. Xiaoting Zhang, Guoxin Fang, Chengkai Dai, Jouke Verlinden, Jun Wu, Emily Whiting, and Charlie CL Wang. 2017. Thermal-comfort design of personalized casts. In Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. 243–254.Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Yunbo Zhang and Tsz-Ho Kwok. 2019. Customization and topology optimization of compression casts/braces on two-manifold surfaces. Computer-Aided Design 111 (2019), 113–122.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Computational Design of Active Kinesthetic Garments

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      UIST '22: Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology
      October 2022
      1363 pages
      ISBN:9781450393201
      DOI:10.1145/3526113

      Copyright © 2022 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 October 2022

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

      Acceptance Rates

      Overall Acceptance Rate842of3,967submissions,21%

      Upcoming Conference

      UIST '24

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format .

    View HTML Format