The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Feedback Control of Soft Robot Actuators via Commercial Flex Bend Sensors
Abstract
Soft robotics is an emerging field that takes advantage of compliant materials and makes use of nonstandard actuators. Flexible fluid actuators (FFAs) use fluid pressure to produce high deformation of elastomeric-based structures. However, closed-loop control of such actuators is still very challenging due to the lack of robust, reliable, and inexpensive sensors that can be integrated onto highly deformable actuator structures, involving very low cost materials and manufacturing. This paper presents a systematic approach to implement the feedback control of FFA-based soft robotic bending modules by using commercial flex bend sensors. A flex bend sensor detects the module curvature in one direction, and its response is processed by an on board microcontroller and sent to the central control system. Such sensor integration enables the closed-loop control of modular robotic architectures, often used in soft robotics. Once integrated with the soft module, the sensor response was calibrated by the use of a ground truth electro-magnetic tracking system in order to characterize its behavior when combined with the relative FFA. A feedback control using a low-pass filter and a proportional-integral controller was designed and used to evaluate the dynamic response and the position accuracy of the integrated module. With such closed-loop control, the module tip is positioned with less than 1 mm accuracy, which can be considered a relevant result in the soft robotics field.
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
Design, fabrication and control of soft robots
Rus, D., & Tolley, M. T. (2015) · Nature · doi:10.1038/nature14543 · Cited by 5,825
Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836
Cited by
Hegde, C., Su, J., Tan, J. M. R., He, K., Chen, X., & Magdassi, S. (2023) · ACS Nano · doi:10.1021/acsnano.3c04089 · Cited by 384
Metadata
- Authors
- Gerboni, G., Diodato, A., Ciuti, G., Cianchetti, M., & Menciassi, A.
- Venue
- IEEE/ASME Transactions on Mechatronics
- Published
- 2017-08
- Volume
- 22
- Issue
- 4
- Pages
- 1881-1888
- ISSN
- 1083-4435 (ISSN-L)
- 1941-014X
- OpenAlex
- W2610150749
- Cited by
- 220
- References
- 2
- FWCI
- 8.50
- Type
- journal article
- Language
- en
- Open access
- closed
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: Feedback Control of Soft Robot Actuators via Commercial Flex Bend Sensors. https://app.cochat.ai/papers/10.1109/tmech.2017.2699677
- The paper
- Gerboni, G., Diodato, A., Ciuti, G., Cianchetti, M., & Menciassi, A. (2017). Feedback Control of Soft Robot Actuators via Commercial Flex Bend Sensors. IEEE/ASME Transactions on Mechatronics. https://doi.org/10.1109/tmech.2017.2699677
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.