Jaime Zabalza
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study.
Zabalza, Jaime; Fei, Zixiang; Wong, Cuebong; Yan, Yijun; Mineo, Carmelo; Yang, Erfu; Rodden, Tony; Mehnen, Jorn; Pham, Quang-Cuong; Ren, Jinchang
Authors
Zixiang Fei
Cuebong Wong
Dr Yijun Yan y.yan2@rgu.ac.uk
Research Fellow
Carmelo Mineo
Erfu Yang
Tony Rodden
Jorn Mehnen
Quang-Cuong Pham
Professor Jinchang Ren j.ren@rgu.ac.uk
Professor of Computing Science
Abstract
Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision allows the detection and localization of a randomly moving obstacle. Path correction to avoid collision avoidance for such obstacles with robotic manipulator is achieved by exploiting an adaptive path planning module along with a dedicated robot control module, where the three modules run simultaneously. These sensing/smart capabilities allow the smooth interactions between the robot and its dynamic environment, where the robot needs to react to dynamic changes through autonomous thinking and reasoning with the reaction times below the average human reaction time. The experimental results demonstrate that effective human-robot and robot-robot interactions can be realized through the innovative integration of emerging sensing techniques, efficient planning algorithms and systematic designs.
Citation
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2019. Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study. Sensors [online], 19(6), article 1354. Available from: https://doi.org/10.3390/s19061354
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 8, 2019 |
Online Publication Date | Mar 18, 2019 |
Publication Date | Mar 31, 2019 |
Deposit Date | May 5, 2022 |
Publicly Available Date | May 5, 2022 |
Journal | Sensors |
Print ISSN | 1424-8220 |
Electronic ISSN | 1424-8220 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 19 |
Issue | 6 |
Article Number | 1354 |
DOI | https://doi.org/10.3390/s19061354 |
Keywords | Adaptive reasoning; Dynamic environments; Human-robot interaction; Path planning; Robot control; Smart sensing |
Public URL | https://rgu-repository.worktribe.com/output/1085403 |
Related Public URLs | https://rgu-repository.worktribe.com/output/1654209 |
Files
ZABALZA 2019 Smart sensing and adaptive (VOR)
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Copyright Statement
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
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