The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies
Open accessAbstract
Tactile sensing is an essential component in human-robot interaction and object manipulation. Soft sensors allow for safe interaction and improved gripping performance. Here we present the TacTip family of sensors: a range of soft optical tactile sensors with various morphologies fabricated through dual-material 3D printing. All of these sensors are inspired by the same biomimetic design principle: transducing deformation of the sensing surface via movement of pins analogous to the function of intermediate ridges within the human fingertip. The performance of the TacTip, TacTip-GR2, TacTip-M2, and TacCylinder sensors is here evaluated and shown to attain submillimeter accuracy on a rolling cylinder task, representing greater than 10-fold super-resolved acuity. A version of the TacTip sensor has also been open-sourced, enabling other laboratories to adopt it as a platform for tactile sensing and manipulation research. These sensors are suitable for real-world applications in tactile perception, exploration, and manipulation, and will enable further research and innovation in the field of soft tactile sensing.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Coding and use of tactile signals from the fingertips in object manipulation tasks
Johansson, R. S., & Flanagan, J. R. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2621 · Cited by 2,063
Tactile Sensing—From Humans to Humanoids
Dahiya, R. S., Metta, G., Valle, M., & Sandini, G. (2010) · IEEE Transactions on Robotics · doi:10.1109/tro.2009.2033627 · Cited by 1,851
The social role of touch in humans and primates: Behavioural function and neurobiological mechanisms
Dunbar, R. I. M. (2010) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2008.07.001 · Cited by 798
Tactile sensing in dexterous robot hands — Review
Kappassov, Z., Corrales, J.-A., & Perdereau, V. (2015) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2015.07.015 · Cited by 782
Extracting object properties through haptic exploration
Lederman, S. J., & Klatzky, R. L. (1993) · Acta Psychologica · doi:10.1016/0001-6918(93)90070-8 · Cited by 401
Retrographic sensing for the measurement of surface texture and shape
Johnson, M. K., & Adelson, E. H. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206534 · Cited by 307
Development of polyimide flexible tactile sensor skin
Engel, J., Chen, J., & Liu, C. (2003) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/13/3/302 · Cited by 291
The Feel of MEMS Barometers: Inexpensive and Easily Customized Tactile Array Sensors
Tenzer, Y., Jentoft, L. P., & Howe, R. D. (2014) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2014.2310152 · Cited by 203
Lee, H.-K., Chung, J., Chang, S.-I., & Yoon, E. (2011) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/21/3/035010 · Cited by 187
The Soft Robotics Toolkit: Shared Resources for Research and Design
Holland, D., Park, E. J., Polygerinos, P., Bennett, G. J., & Walsh, C. J. (2014) · Soft Robotics · doi:10.1089/soro.2014.0010 · Cited by 158
Cited by
Lambeta, M., Chou, P.-W., Tian, S., Yang, B., Maloon, B., Most, V. R., Stroud, D., Santos, R., Byagowi, A., Kammerer, G., et al. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2977257 · Cited by 553
Recent Progress in Advanced Tactile Sensing Technologies for Soft Grippers
Qu, J., Mao, B., Li, Z., Xu, Y., Zhou, K., Cao, X., Fan, Q., Xu, M., Liang, B., Liu, H., et al. (2023) · Advanced Functional Materials · doi:10.1002/adfm.202306249 · Cited by 259
Sim-to-Real Transfer for Optical Tactile Sensing
Ding, Z., Lepora, N. F., & Johns, E. (2020) · 2020 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra40945.2020.9197512 · Cited by 53
Self-citationMultimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
Erickson, Z., Xing, E., Srirangam, B., Chernova, S., & Kemp, C. C. (2020) · 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341165 · Cited by 50
Using 3D Convolutional Neural Networks for Tactile Object Recognition with Robotic Palpation
Pastor, F., Gandarias, J. M., García-Cerezo, A. J., & Gómez-de-Gabriel, J. M. (2019) · Sensors · doi:10.3390/s19245356 · Cited by 49
Metadata
- Authors
- Ward-Cherrier, B., Pestell, N., Cramphorn, L., Winstone, B., Giannaccini, M. E., Rossiter, J., & Lepora, N. F.
- Venue
- Soft Robotics
- Publisher
- SAGE Publications
- Published
- 2018-04
- Volume
- 5
- Issue
- 2
- Pages
- 216-227
- ISSN
- 2169-5172 (ISSN-L)
- 2169-5180
- OpenAlex
- W2781493652
- Cited by
- 587
- References
- 31
- FWCI
- 14.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies. https://app.cochat.ai/papers/10.1089/soro.2017.0052
- The paper
- Ward-Cherrier, B., Pestell, N., Cramphorn, L., Winstone, B., Giannaccini, M. E., Rossiter, J., & Lepora, N. F. (2018). The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies. Soft Robotics. https://doi.org/10.1089/soro.2017.0052
Data sources
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.
