On Inferring Intentions in Shared Tasks for Industrial Collaborative Robots
Open accessAbstract
Inferring human operators’ actions in shared collaborative tasks plays a crucial role in enhancing the cognitive capabilities of industrial robots. In all these incipient collaborative robotic applications, humans and robots not only should share space, but also forces and the execution of a task. In this article, we present a robotic system that is able to identify different human’s intentions and to adapt its behavior consequently, only employing force data. In order to accomplish this aim, three major contributions are presented: (a) a force based operator’s intention recognition system based on data from only two users; (b) a force based dataset of physical human–robot interaction; and (c) validation of the whole system with 15 people in a scenario inspired by a realistic industrial application. This work is an important step towards a more natural and user-friendly manner of physical human–robot interaction in scenarios where humans and robots collaborate in the accomplishment of a task.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In industrial robotics, five typical levels of human-robot cooperation are defined: no collaboration; coexistence; synchronisation; cooperation; collaboration.
“In industrial robotics, five typical levels of human-robot cooperation are defined (Figure 2): (i) no collaboration; (ii) coexistence; (iii) synchronisation; (iv) cooperation; (v) collaboration [5].”
From Advanced Applications of Industrial Robotics: New Trends and Possibilities (2021) · cites this paper as [5]
Cites
Bagnall, A., Lines, J., Bostrom, A., Large, J., & Keogh, E. (2017) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-016-0483-9 · Cited by 1,377 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Advanced Applications of Industrial Robotics: New Trends and Possibilities
Dzedzickis, A., Subačiūtė-Žemaitienė, J., Šutinys, E., Samukaitė-Bubnienė, U., & Bučinskas, V. (2021) · Applied Sciences · doi:10.3390/app12010135 · Cited by 228 · see citing works
- Authors
- Olivares-Alarcos, A., Foix, S., & Alenyà, G.
- Affiliations
- Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens i Artigas 4-6, 08028 Barcelona, Spain
- Consejo Superior de Investigaciones Científicas (ES)
- Venue
- Electronics
- Publisher
- MDPI AG
- Published
- 2019-11-07
- Volume
- 8
- Issue
- 11
- Pages
- 1306
- ISSN
- 2079-9292 (ISSN-L)
- OpenAlex
- W2982783879
- Cited by
- 20
- References
- 1
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 1 · 2023: 2 · 2022: 5 · 2021: 4 · 2020: 3
- FWCI
- 1.61
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Electronics (publishedVersion, cc-by)
- UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by-nc-nd)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Regional Catalan Agency ACCIÓ (COMRDI16-1-0017)
- Agencia Estatal de Investigación (MDM-2016-0656, TIN2017-90086-R)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Keywords
- human intention recognition, collaborative robots, human-robot interaction, force sensing, shared task, industrial robots, robot behavior adaptation
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
