Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study

Jaime Zabalza; Zixiang Fei; Cuebong Wong; Yijun Yan; Carmelo Mineo; Erfu Yang; Tony Rodden; Jorn Mehnen; Quang Cuong Pham; Jinchang Ren

doi:10.1007/978-3-030-00563-4_77

Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study

Jaime Zabalza, Zixiang Fei, Cuebong Wong, Yijun Yan, Carmelo Mineo, Erfu Yang (Lead / Corresponding author), Tony Rodden, Jorn Mehnen, Quang Cuong Pham, Jinchang Ren

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Advances in Brain Inspired Cognitive Systems
Subtitle of host publication	9th International Conference, BICS 2018, Proceedings
Editors	Amir Hussain, Bin Luo, Jiangbin Zheng, Xinbo Zhao, Cheng-Lin Liu, Jinchang Ren, Huimin Zhao
Place of Publication	Switzerland
Publisher	Springer
Pages	790-800
Number of pages	11
Edition	1
ISBN (Electronic)	9783030005634
ISBN (Print)	9783030005627
DOIs	https://doi.org/10.1007/978-3-030-00563-4_77
Publication status	Published - 2018
Event	9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018 - Xi'an, China Duration: 7 Jul 2018 → 8 Jul 2018

Publication series

Name	Lecture Notes in Computer Science
Volume	10989
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018
Country/Territory	China
City	Xi'an
Period	7/07/18 → 8/07/18

Keywords

Adaptive reasoning
Dynamic environment
Machine vision
Path planning
Robot control

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-00563-4_77

Cite this

Zabalza, J., Fei, Z., Wong, C., Yan, Y., Mineo, C., Yang, E., Rodden, T., Mehnen, J., Pham, Q. C., & Ren, J. (2018). Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study. In A. Hussain, B. Luo, J. Zheng, X. Zhao, C.-L. Liu, J. Ren, & H. Zhao (Eds.), Advances in Brain Inspired Cognitive Systems: 9th International Conference, BICS 2018, Proceedings (1 ed., pp. 790-800). (Lecture Notes in Computer Science; Vol. 10989). Springer . https://doi.org/10.1007/978-3-030-00563-4_77

Zabalza, Jaime ; Fei, Zixiang ; Wong, Cuebong et al. / Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments : A Case Study. Advances in Brain Inspired Cognitive Systems: 9th International Conference, BICS 2018, Proceedings. editor / Amir Hussain ; Bin Luo ; Jiangbin Zheng ; Xinbo Zhao ; Cheng-Lin Liu ; Jinchang Ren ; Huimin Zhao. 1. ed. Switzerland : Springer , 2018. pp. 790-800 (Lecture Notes in Computer Science).

@inproceedings{c128c96362c345c6b153e1246b799e2f,

title = "Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study",

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.",

keywords = "Adaptive reasoning, Dynamic environment, Machine vision, Path planning, Robot control",

author = "Jaime Zabalza and Zixiang Fei and Cuebong Wong and Yijun Yan and Carmelo Mineo and Erfu Yang and Tony Rodden and Jorn Mehnen and Pham, {Quang Cuong} and Jinchang Ren",

note = "Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; 9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018 ; Conference date: 07-07-2018 Through 08-07-2018",

year = "2018",

doi = "10.1007/978-3-030-00563-4_77",

language = "English",

isbn = "9783030005627",

series = "Lecture Notes in Computer Science",

publisher = "Springer ",

pages = "790--800",

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booktitle = "Advances in Brain Inspired Cognitive Systems",

edition = "1",

}

Zabalza, J, Fei, Z, Wong, C, Yan, Y, Mineo, C, Yang, E, Rodden, T, Mehnen, J, Pham, QC & Ren, J 2018, Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study. in A Hussain, B Luo, J Zheng, X Zhao, C-L Liu, J Ren & H Zhao (eds), Advances in Brain Inspired Cognitive Systems: 9th International Conference, BICS 2018, Proceedings. 1 edn, Lecture Notes in Computer Science, vol. 10989, Springer , Switzerland, pp. 790-800, 9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018, Xi'an, China, 7/07/18. https://doi.org/10.1007/978-3-030-00563-4_77

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 et al.
Advances in Brain Inspired Cognitive Systems: 9th International Conference, BICS 2018, Proceedings. ed. / Amir Hussain; Bin Luo; Jiangbin Zheng; Xinbo Zhao; Cheng-Lin Liu; Jinchang Ren; Huimin Zhao. 1. ed. Switzerland: Springer , 2018. p. 790-800 (Lecture Notes in Computer Science; Vol. 10989).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments

T2 - 9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018

AU - Zabalza, Jaime

AU - Fei, Zixiang

AU - Wong, Cuebong

AU - Yan, Yijun

AU - Mineo, Carmelo

AU - Yang, Erfu

AU - Rodden, Tony

AU - Mehnen, Jorn

AU - Pham, Quang Cuong

AU - Ren, Jinchang

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Adaptive reasoning

KW - Dynamic environment

KW - Machine vision

KW - Path planning

KW - Robot control

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DO - 10.1007/978-3-030-00563-4_77

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AN - SCOPUS:85055123731

SN - 9783030005627

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EP - 800

BT - Advances in Brain Inspired Cognitive Systems

A2 - Hussain, Amir

A2 - Luo, Bin

A2 - Zheng, Jiangbin

A2 - Zhao, Xinbo

A2 - Liu, Cheng-Lin

A2 - Ren, Jinchang

A2 - Zhao, Huimin

PB - Springer

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Y2 - 7 July 2018 through 8 July 2018

ER -

Zabalza J, Fei Z, Wong C, Yan Y, Mineo C, Yang E et al. Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study. In Hussain A, Luo B, Zheng J, Zhao X, Liu CL, Ren J, Zhao H, editors, Advances in Brain Inspired Cognitive Systems: 9th International Conference, BICS 2018, Proceedings. 1 ed. Switzerland: Springer . 2018. p. 790-800. (Lecture Notes in Computer Science). Epub 2018 Oct 6. doi: 10.1007/978-3-030-00563-4_77

Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study

Abstract

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Keywords

ASJC Scopus subject areas

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