Seamless Human–Robot Interaction
Springer Series in Advanced Manufacturing, ISSN: 2196-1735, Page: 289-307
2021
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures3
- Readers3
Book Chapter Description
This chapter focuses on human–robot interaction technologies that could seamlessly support operators on their activities in a production line. The key technology that has been mobilized is Augmented Reality (AR), due to its intuitiveness and the easiness that can overlay digital information on real assets, giving more mature support to the operators. Also, another benefit of AR technology, is that operators can receive this information using wearable devices when needed, avoiding losing time waiting or moving around the assembly station where a fixed control PC exists. Following a literature review, it is described the initialization phase of an AR application, through which the system can understand the personal characteristics of the operator (such as his/her height), to give him/her a realistic feeling when the digital components are overlaid on the real ones. Additionally, during this phase, the system receives information about the station where the operator is located, to provide the respective information. Later, support functionalities for both programming and execution phases of the production are described, as well as a brief description of the software platform to which all the tools have been integrated. Lastly, a couple of use cases stemming from the automotive industry prove the described concept.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85151493476&origin=inward; http://dx.doi.org/10.1007/978-3-030-51591-1_15; http://link.springer.com/10.1007/978-3-030-51591-1_15; http://link.springer.com/content/pdf/10.1007/978-3-030-51591-1_15; https://dx.doi.org/10.1007/978-3-030-51591-1_15; https://link.springer.com/chapter/10.1007/978-3-030-51591-1_15
Springer Science and Business Media LLC
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