The DOI matches its Crossref record; 94 of the 94 references it cites were found in a registry or an index.
Gesture recognition for human-robot collaboration: A review
Abstract
Abstract Recently, the concept of human-robot collaboration has raised many research interests. Instead of robots replacing human workers in workplaces, human-robot collaboration allows human workers and robots working together in a shared manufacturing environment. Human-robot collaboration can release human workers from heavy tasks with assistive robots if effective communication channels between humans and robots are established. Although the communication channels between human workers and robots are still limited, gesture recognition has been effectively applied as the interface between humans and computers for long time. Covering some of the most important technologies and algorithms of gesture recognition, this paper is intended to provide an overview of the gesture recognition research and explore the possibility to apply gesture recognition in human-robot collaborative manufacturing. In this paper, an overall model of gesture recognition for human-robot collaboration is also proposed. There are four essential technical components in the model of gesture recognition for human-robot collaboration: sensor technologies, gesture identification, gesture tracking and gesture classification. Reviewed approaches are classified according to the four essential technical components. Statistical analysis is also presented after technical analysis. Towards the end of this paper, future research trends are outlined.
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1 retracted
RETRACTED ARTICLE: Static hand gesture recognition using neural networks
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“Learning algorithms such as Support Vector Machine (SVM), Arti fi cial Neural Networks (ANN) and Random Decision Forests (RDF) are widely applied in gesture recognition systems (Ronfard et al., 2002; Lee et al., 2003; Tang et al., 2014).”
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Cited by
Cobot programming for collaborative industrial tasks: An overview
El Zaatari, S., Marei, M., Li, W., & Usman, Z. (2019) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2019.03.003 · Cited by 470
Human motion prediction for human-robot collaboration
Liu, H., & Wang, L. (2017) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2017.04.009 · Cited by 193
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Metadata
- Authors
- Liu, H., & Wang, L.
- Venue
- International Journal of Industrial Ergonomics
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 68
- Pages
- 355-367
- ISSN
- 0169-8141 (ISSN-L)
- OpenAlex
- W2592523922
- Cited by
- 422
- References
- 94
- FWCI
- 44.71
- Type
- journal article
- Language
- en
- Open access
- closed
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