Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/94103
Title: Edge intelligence and agnostic robotic paradigm in resource synchronisation and sharing in flexible robotic and facility control system
Authors: Keung, KL 
Chan, YY 
Ng, KKH 
Mak, SL
Li, CH
Qin, Y 
Yu, CW 
Issue Date: Apr-2022
Source: Advanced engineering informatics, Apr. 2022, v. 52, 101530
Abstract: 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.
Keywords: Agnostic robotic paradigm
Cloud-edge computing
Flexible robotic and facility control system
Robotic mobile fulfilment system
Unmanned ground vehicles
Publisher: Elsevier
Journal: Advanced engineering informatics 
EISSN: 1474-0346
DOI: 10.1016/j.aei.2022.101530
Appears in Collections:Journal/Magazine Article

Open Access Information
Status embargoed access
Embargo End Date 2024-04-30
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

52
Last Week
1
Last month
Citations as of May 5, 2024

SCOPUSTM   
Citations

21
Citations as of May 3, 2024

WEB OF SCIENCETM
Citations

15
Citations as of May 2, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.