Edge intelligence and agnostic robotic paradigm in resource synchronisation and sharing in flexible robotic and facility control system

K. L. Keung, Y. Y. Chan, Kam K.H. Ng, S. L. Mak, C. H. Li, Yichen Qin, C. W. Yu

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

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.

Original languageEnglish
Article number101530
JournalAdvanced Engineering Informatics
Volume52
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Agnostic robotic paradigm
  • Cloud-edge computing
  • Flexible robotic and facility control system
  • Robotic mobile fulfilment system
  • Unmanned ground vehicles

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