The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Soft robot perception using embedded soft sensors and recurrent neural networks
Abstract
Recurrent neural networks with an unstructured redundant soft sensor topology allow robust multimodal proprioceptive capabilities.
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Cites
Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
Design, fabrication and control of soft robots
Rus, D., & Tolley, M. T. (2015) · Nature · doi:10.1038/nature14543 · Cited by 5,825
Self-citationA Learning Algorithm for Continually Running Fully Recurrent Neural Networks
Williams, R. J., & Zipser, D. (1989) · Neural Computation · doi:10.1162/neco.1989.1.2.270 · Cited by 4,369
A stretchable carbon nanotube strain sensor for human-motion detection
Yamada, T., Hayamizu, Y., Yamamoto, Y., Yomogida, Y., Izadi-Najafabadi, A., Futaba, D. N., & Hata, K. (2011) · Nature Nanotechnology · doi:10.1038/nnano.2011.36 · Cited by 3,247
Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review
Amjadi, M., Kyung, K., Park, I., & Sitti, M. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201504755 · Cited by 3,202
Proske, U., & Gandevia, S. C. (2012) · Physiological Reviews · doi:10.1152/physrev.00048.2011 · Cited by 2,223
Shepherd, R. F., Ilievski, F., Choi, W., Morin, S. A., Stokes, A. A., Mazzeo, A. D., Chen, X., Wang, M., & Whitesides, G. M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1116564108 · Cited by 2,111
Embedded 3D Printing of Strain Sensors within Highly Stretchable Elastomers
Muth, J. T., Vogt, D. M., Truby, R. L., Mengüç, Y., Kolesky, D. B., Wood, R. J., & Lewis, J. A. (2014) · Advanced Materials · doi:10.1002/adma.201400334 · Cited by 1,611
Soft robotics: Technologies and systems pushing the boundaries of robot abilities
Laschi, C., Mazzolai, B., & Cianchetti, M. (2016) · Science Robotics · doi:10.1126/scirobotics.aah3690 · Cited by 1,570 · cited 1×
“With the rise of soft robotics and the complexities involved with modeling and development of soft robots (1, 2), we are presented with new challenges in perception.”
BackgroundSelf-citationPolygerinos, P., Correll, N., Morin, S. A., Mosadegh, B., Onal, C. D., Petersen, K., Cianchetti, M., Tolley, M. T., & Shepherd, R. F. (2017) · Advanced Engineering Materials · doi:10.1002/adem.201700016 · Cited by 1,063
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Cited by
Zhu, M., Sun, Z., Zhang, Z., Shi, Q., He, T., Liu, H., Chen, T., & Lee, C. (2020) · Science Advances · doi:10.1126/sciadv.aaz8693 · Cited by 784
Electronic skins and machine learning for intelligent soft robots
Shih, B., Shah, D., Li, J., Thuruthel, T. G., Park, Y.-L., Iida, F., Bao, Z., Kramer-Bottiglio, R., & Tolley, M. T. (2020) · Science Robotics · doi:10.1126/scirobotics.aaz9239 · Cited by 715
Self-citationTriboelectric nanogenerator sensors for soft robotics aiming at digital twin applications
Jin, T., Sun, Z., Li, L., Zhang, Q., Zhu, M., Zhang, Z., Yuan, G., Chen, T., Tian, Y., Hou, X., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19059-3 · Cited by 695
High‐Stretchability, Ultralow‐Hysteresis ConductingPolymer Hydrogel Strain Sensors for Soft Machines
Shen, Z., Zhang, Z., Zhang, N., Li, J., Zhou, P., Hu, F., Rong, Y., Lu, B., & Gu, G. (2022) · Advanced Materials · doi:10.1002/adma.202203650 · Cited by 574
Cutaneous Ionogel Mechanoreceptors for Soft Machines, Physiological Sensing, and Amputee Prostheses
Shen, Z., Zhu, X., Majidi, C., & Gu, G. (2021) · Advanced Materials · doi:10.1002/adma.202102069 · Cited by 291
Metadata
- Authors
- Thuruthel, T. G., Shih, B., Laschi, C., & Tolley, M. T.
- Venue
- Science Robotics
- Published
- 2019-01-30
- Volume
- 4
- Issue
- 26
- ISSN
- 2470-9476 (ISSN-L)
- OpenAlex
- W2913446864
- Cited by
- 678
- References
- 41
- FWCI
- 23.72
- Type
- journal article
- Language
- en
- Open access
- closed
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- Thuruthel, T. G., Shih, B., Laschi, C., & Tolley, M. T. (2019). Soft robot perception using embedded soft sensors and recurrent neural networks. Science Robotics. https://doi.org/10.1126/scirobotics.aav1488
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
