The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment
Abstract
Leveraging the elastic bodies of soft robots promises to enable the execution of dynamic motions as well as compliant and safe interaction with an unstructured environment. However, the exploitation of these abilities is constrained by the lack of appropriate control strategies. This work tackles for the first time the development of closed-loop dynamic controllers for a continuous soft robot. We present two architectures designed for dynamic trajectory tracking and surface following, respectively. Both controllers are designed to preserve the natural softness of the robot and adapt to interactions with an unstructured environment. The validity of the controllers is proven analytically within the hypotheses of the model. The controllers are evaluated through an extensive series of simulations, and through experiments on a physical soft robot capable of planar motions.
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
Self-citationSoft 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×
“Inspired by biology and with the aim of reaching a higher level of agility and compliance, researchers are designing soft robots with elastic bodies (Laschi et al., 2016; Polygerinos et al., 2017; Rus and Tolley, 2015).”
Meshworm: A Peristaltic Soft Robot With Antagonistic Nickel Titanium Coil Actuators
Seok, S., Onal, C. D., Cho, K.-J., Wood, R. J., Rus, D., & Kim, S. (2013) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2012.2204070 · Cited by 665 · cited 2×
“However, despite the emergence of several soft robotic hardware architectures (Holland et al., 2017; Homberg et al., 2019; Katzschmann et al., 2018; Laschi et al., 2012; Seok et al., 2013), examples that show the execution of dynamic movements and controlled compliant interaction with the environment are still missing.”
BackgroundSelf-citationDesign, kinematics, and control of a soft spatial fluidic elastomer manipulator
Marchese, A. D., & Rus, D. (2016) · The International Journal of Robotics Research · doi:10.1177/0278364915587925 · Cited by 330
Self-citation
Cited by
Octopus-inspired sensorized soft arm for environmental interaction
Xie, Z., Yuan, F., Liu, J., Tian, L., Chen, B., Fu, Z., Mao, S., Jin, T., Wang, Y., He, X., et al. (2023) · Science Robotics · doi:10.1126/scirobotics.adh7852 · Cited by 299
Metadata
- Authors
- Della Santina, C., Katzschmann, R. K., Bicchi, A., & Rus, D.
- Venue
- The International Journal of Robotics Research
- Publisher
- SAGE Publications
- Published
- 2020-01-11
- Volume
- 39
- Issue
- 4
- Pages
- 490-513
- ISSN
- 0278-3649 (ISSN-L)
- 1741-3176
- OpenAlex
- W3000160985
- Cited by
- 295
- References
- 4
- FWCI
- 12.16
- 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: Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment. https://app.cochat.ai/papers/10.1177/0278364919897292
- The paper
- Della Santina, C., Katzschmann, R. K., Bicchi, A., & Rus, D. (2020). Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment. The International Journal of Robotics Research. https://doi.org/10.1177/0278364919897292
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.
