Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study
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...
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sg-ntu-dr.10356-1059302023-03-04T17:14:56Z 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 School of Mechanical and Aerospace Engineering Adaptive Reasoning Dynamic Environments DRNTU::Engineering::Mechanical engineering 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. Published version 2019-06-14T08:02:31Z 2019-12-06T22:00:55Z 2019-06-14T08:02:31Z 2019-12-06T22:00:55Z 2019 Journal Article Zabalza, J., Fei, Z., Wong, C., Yan, Y., Mineo, C., Yang, E., . . . Ren, J. (2019). Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study. Sensors, 19(6), 1354-. doi:10.3390/s19061354 1424-8220 https://hdl.handle.net/10356/105930 http://hdl.handle.net/10220/48779 10.3390/s19061354 en Sensors © 2019 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 23 p. application/pdf |
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Adaptive Reasoning Dynamic Environments DRNTU::Engineering::Mechanical engineering Zabalza, Jaime Fei, Zixiang Wong, Cuebong Yan, Yijun Mineo, Carmelo Yang, Erfu Rodden, Tony Mehnen, Jorn Pham, Quang-Cuong Ren, Jinchang Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
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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. |
author2 |
School of Mechanical and Aerospace Engineering |
author_facet |
School of Mechanical and Aerospace Engineering Zabalza, Jaime Fei, Zixiang Wong, Cuebong Yan, Yijun Mineo, Carmelo Yang, Erfu Rodden, Tony Mehnen, Jorn Pham, Quang-Cuong Ren, Jinchang |
format |
Article |
author |
Zabalza, Jaime Fei, Zixiang Wong, Cuebong Yan, Yijun Mineo, Carmelo Yang, Erfu Rodden, Tony Mehnen, Jorn Pham, Quang-Cuong Ren, Jinchang |
author_sort |
Zabalza, Jaime |
title |
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
title_short |
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
title_full |
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
title_fullStr |
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
title_full_unstemmed |
Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
title_sort |
smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study |
publishDate |
2019 |
url |
https://hdl.handle.net/10356/105930 http://hdl.handle.net/10220/48779 |
_version_ |
1759856505882935296 |