The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Challenges and Outlook in Robotic Manipulation of Deformable Objects
Open accessAbstract
Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new applications in the industrial, services, and health-care sectors. However, compared to rigid object manipulation, the manipulation of deformable objects is considerably more complex and is still an open research problem. Addressing DOM challenges demands breakthroughs in almost all aspects of robotics: hardware design, sensing, (deformation) modeling, planning, and control. In this article, we review recent advances and highlight the main challenges when considering deformation in each subfield. A particular focus of our article lies in the discussions of these challenges and proposing future directions of research.
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Citations
Cites
GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force
Yuan, W., Dong, S., & Adelson, E. (2017) · Sensors · doi:10.3390/s17122762 · Cited by 1,166
Self-citationOptoelectronically innervated soft prosthetic hand via stretchable optical waveguides
Zhao, H., O’Brien, K., Li, S., & Shepherd, R. F. (2016) · Science Robotics · doi:10.1126/scirobotics.aai7529 · Cited by 982
Interaction Networks for Learning about Objects, Relations and Physics
Battaglia, P. W., Pascanu, R., Lai, M., Rezende, D., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1612.00222 · Cited by 969
Sanchez, J., Corrales, J.-A., Bouzgarrou, B.-C., & Mezouar, Y. (2018) · The International Journal of Robotics Research · doi:10.1177/0278364918779698 · Cited by 457
Ultragentle manipulation of delicate structures using a soft robotic gripper
Sinatra, N. R., Teeple, C. B., Vogt, D. M., Parker, K. K., Gruber, D. F., & Wood, R. J. (2019) · Science Robotics · doi:10.1126/scirobotics.aax5425 · Cited by 356
Bajcsy, R., Aloimonos, Y., & Tsotsos, J. K. (2018) · Autonomous Robots · doi:10.1007/s10514-017-9615-3 · Cited by 328
Modeling, learning, perception, and control methods for deformable object manipulation
Yin, H., Varava, A., & Kragic, D. (2021) · Science Robotics · doi:10.1126/scirobotics.abd8803 · Cited by 299
Combining self-supervised learning and imitation for vision-based rope manipulation
Nair, A., Chen, D., Agrawal, P., Isola, P., Abbeel, P., Malik, J., & Levine, S. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2017.7989247 · Cited by 255
A Dexterous Soft Robotic Hand for Delicate In-Hand Manipulation
Abondance, S., Teeple, C. B., & Wood, R. J. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.3007411 · Cited by 253
Software toolkit for modeling, simulation, and control of soft robots
Coevoet, E., Morales-Bieze, T., Largilliere, F., Zhang, Z., Thieffry, M., Sanz-Lopez, M., Carrez, B., Marchal, D., Goury, O., Dequidt, J., et al. (2017) · Advanced Robotics · doi:10.1080/01691864.2017.1395362 · Cited by 244
Cited by
SpeedFolding: Learning Efficient Bimanual Folding of Garments
Avigal, Y., Berscheid, L., Asfour, T., Kröger, T., & Goldberg, K. (2022) · 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981402 · Cited by 95
Kadi, H. A., & Terzić, K. (2023) · Sensors · doi:10.3390/s23052389 · Cited by 27
“Zhu et al. (2022) [17] discuss the challenges posed by different types of DO manipulation in terms of perception, modelling and manipulation.”
BackgroundInteractive Perception for Deformable Object Manipulation
Weng, Z., Zhou, P., Yin, H., Kravberg, A., Varava, A., Navarro-Alarcon, D., & Kragic, D. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3431943 · Cited by 7
“Interactive Perception and manipulation of deformable objects [7], [8], [9], [10] are commonly studied as two separate problems in the robotics community.”
BackgroundGoal-Conditioned Model Simplification for 1-D and 2-D Deformable Object Manipulation
Wang, S., Leonetti, M., & Dogar, M. (2025) · IEEE Transactions on Robotics · doi:10.1109/tro.2025.3577052 · Cited by 4
“14 and 15.”
A Perspective on Open Challenges in Deformable Object Manipulation
McKennaa, R. P., & Oyekan, J. (2026) · arXiv · doi:10.48550/arxiv.2602.22998 · Cited by 1
“While previous reviews [2], [17] provided broad coverage of the subject, their emphasis was primarily on analytical methods.”
Metadata
- Authors
- Zhu, J., Cherubini, A., Dune, C., Navarro-Alarcon, D., Alambeigi, F., Berenson, D., Ficuciello, F., Harada, K., Kober, J., Li, X., Pan, J., Yuan, W., & Gienger, M.
- Venue
- IEEE Robotics & Automation Magazine
- Published
- 2022-09
- Volume
- 29
- Issue
- 3
- Pages
- 67-77
- ISSN
- 1070-9932 (ISSN-L)
- 1558-223X
- OpenAlex
- W3159812989
- Cited by
- 265
- References
- 73
- FWCI
- 22.83
- Type
- journal article
- Language
- en
- Open access
- green
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- Zhu, J., Cherubini, A., Dune, C., Navarro-Alarcon, D., Alambeigi, F., Berenson, D., Ficuciello, F., Harada, K., Kober, J., Li, X., Pan, J., Yuan, W., & Gienger, M. (2022). Challenges and Outlook in Robotic Manipulation of Deformable Objects. IEEE Robotics & Automation Magazine. https://doi.org/10.1109/mra.2022.3147415
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