TY - JOUR
T1 - Edge intelligence and agnostic robotic paradigm in resource synchronisation and sharing in flexible robotic and facility control system
AU - Keung, K. L.
AU - Chan, Y. Y.
AU - Ng, Kam K.H.
AU - Mak, S. L.
AU - Li, C. H.
AU - Qin, Yichen
AU - Yu, C. W.
N1 - Funding Information:
The research is supported by the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong SAR. Our gratitude is also extended to the Research Committee of the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University and the Innovation and Technology Fund – Partnership Research Programme (ITF-PRP), Innovation and Technology Commission, HK Government, HKSAR for support of the project (PRP/102/20FX); the Natural Science Foundation of China (72101144) and Shanghai Pujiang Program (21PJC067). The research is partially supported by student project codes (RJ1D). The authors would like to express their appreciation to the anonymous case company for their assistance with the data collection.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/4
Y1 - 2022/4
N2 - The agnostic robotic paradigm (ARP) represents a recent development as the use of robots becomes more common, and there is a need for agnostic robots to cope with rich artificial objects environments. All parties and stakeholders need to seize the imminent opportunity and act on ushering in the revolutionary changes of contemporary robotic and facility control solutions. The scalability and effectiveness of robotic enterprise solutions depend primarily on the availability of operational information, robotic solutions, and their information infrastructure. However, different functions and software of robotics and facilities are being launched in the market. Therefore, this paper investigates the implementation of the emerging ARP for the Industrial Internet of Things (IIoT) and resource synchronisation flexible robotic and facility control system to address this challenge. We propose an Artificial Intelligence (AI) edge intelligence and IIoT-based agnostic robotic architecture for resource synchronisation and sharing in manufacturing and robotic mobile fulfillment systems (RMFS). We adopted simultaneous localisation and mapping (SLAM) as one of the edge intelligence, provided the simulation results, and tested with multiple parameters under different conflicts. Our research suggests that purposely developing an ARP for flexible robotic and facility control system via IIoT assisted with AI-edge intelligence are a good solution for both operational and management level under a cloud platform.
AB - The agnostic robotic paradigm (ARP) represents a recent development as the use of robots becomes more common, and there is a need for agnostic robots to cope with rich artificial objects environments. All parties and stakeholders need to seize the imminent opportunity and act on ushering in the revolutionary changes of contemporary robotic and facility control solutions. The scalability and effectiveness of robotic enterprise solutions depend primarily on the availability of operational information, robotic solutions, and their information infrastructure. However, different functions and software of robotics and facilities are being launched in the market. Therefore, this paper investigates the implementation of the emerging ARP for the Industrial Internet of Things (IIoT) and resource synchronisation flexible robotic and facility control system to address this challenge. We propose an Artificial Intelligence (AI) edge intelligence and IIoT-based agnostic robotic architecture for resource synchronisation and sharing in manufacturing and robotic mobile fulfillment systems (RMFS). We adopted simultaneous localisation and mapping (SLAM) as one of the edge intelligence, provided the simulation results, and tested with multiple parameters under different conflicts. Our research suggests that purposely developing an ARP for flexible robotic and facility control system via IIoT assisted with AI-edge intelligence are a good solution for both operational and management level under a cloud platform.
KW - Agnostic robotic paradigm
KW - Cloud-edge computing
KW - Flexible robotic and facility control system
KW - Robotic mobile fulfilment system
KW - Unmanned ground vehicles
UR - http://www.scopus.com/inward/record.url?scp=85124472560&partnerID=8YFLogxK
U2 - 10.1016/j.aei.2022.101530
DO - 10.1016/j.aei.2022.101530
M3 - Journal article
AN - SCOPUS:85124472560
SN - 1474-0346
VL - 52
JO - Advanced Engineering Informatics
JF - Advanced Engineering Informatics
M1 - 101530
ER -