Jaime Zabalza
Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks 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
In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on machine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.
Citation
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2018. Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study. In Ren, J., Hussain, A., Zheng, J., Liu, C.-L., Lou, B., Zhao, H. and Zhao, X. (eds.) Advances in brain inspired cognitive systems: proceedings of 9th International conference on Brain inspired cognitive system 2018 (BICS2018), 7-8 July 2018, Xi'an, China. Lecture notes in computer science, 10989. Cham: Springer [online], pages 790-800. Available from: https://doi.org/10.1007/978-3-030-00563-4_77
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 9th International conference on Brain inspired cognitive system 2018 (BICS2018) |
Start Date | Jul 7, 2018 |
End Date | Jul 8, 2018 |
Acceptance Date | Jun 16, 2018 |
Online Publication Date | Oct 6, 2018 |
Publication Date | Dec 31, 2018 |
Deposit Date | May 5, 2022 |
Publicly Available Date | May 5, 2022 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 10989 |
Pages | 790-800 |
Series Title | Lecture notes in computer science |
Series ISSN | 0302-9743 |
Book Title | Advances in brain inspired cognitive systems: proceedings of 9th International conference on Brain inspired cognitive system 2018 (BICS2018), 7-8 July 2018, Xi'an, China |
ISBN | 9783030005627 |
DOI | https://doi.org/10.1007/978-3-030-00563-4_77 |
Keywords | Machine vision; Path planning; Robot control; Adaptive reasoning; Dynamic environment |
Public URL | https://rgu-repository.worktribe.com/output/1654258 |
Related Public URLs | https://rgu-repository.worktribe.com/output/1654209 |
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Copyright Statement
The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-00563-4_77. This accepted manuscript is subject to Springer Nature's AM terms of use.
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