Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105930
Title: Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments — a case study
Authors: Zabalza, Jaime
Fei, Zixiang
Wong, Cuebong
Yan, Yijun
Mineo, Carmelo
Yang, Erfu
Rodden, Tony
Mehnen, Jorn
Pham, Quang-Cuong
Ren, Jinchang
Keywords: Adaptive Reasoning
Dynamic Environments
DRNTU::Engineering::Mechanical engineering
Issue Date: 2019
Source: 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
Series/Report no.: Sensors
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.
URI: https://hdl.handle.net/10356/105930
http://hdl.handle.net/10220/48779
ISSN: 1424-8220
DOI: 10.3390/s19061354
Rights: © 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/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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