Camera Arrangement Optimization for Workspace Monitoring in Human-Robot Collaboration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F23%3A10250925" target="_blank" >RIV/61989100:27230/23:10250925 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/1424-8220/23/1/295" target="_blank" >https://www.mdpi.com/1424-8220/23/1/295</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s23010295" target="_blank" >10.3390/s23010295</a>
Alternative languages
Result language
angličtina
Original language name
Camera Arrangement Optimization for Workspace Monitoring in Human-Robot Collaboration
Original language description
Human-robot interaction is becoming an integral part of practice. There is a greater emphasis on safety in workplaces where a robot may bump into a worker. In practice, there are solutions that control the robot based on the potential energy in a collision or a robot re-planning the straight-line trajectory. However, a sensor system must be designed to detect obstacles across the human-robot shared workspace. So far, there is no procedure that engineers can follow in practice to deploy sensors ideally. We come up with the idea of classifying the space as an importance index, which determines what part of the workspace sensors should sense to ensure ideal obstacle sensing. Then, the ideal camera positions can be automatically found according to this classified map. Based on the experiment, the coverage of the important volume by the calculated camera position in the workspace was found to be on average 37% greater compared to a camera placed intuitively by test subjects. Using two cameras at the workplace, the calculated positions were 27% more effective than the subjects' camera positions. Furthermore, for three cameras, the calculated positions were 13% better than the subjects' camera positions, with a total coverage of more than 99% of the classified map.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
<a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sensors
ISSN
1424-3210
e-ISSN
1424-8220
Volume of the periodical
23
Issue of the periodical within the volume
1
Country of publishing house
CH - SWITZERLAND
Number of pages
19
Pages from-to
1-19
UT code for WoS article
000909987000001
EID of the result in the Scopus database
2-s2.0-85145981166