Perspective of self-learning robotics for disassembly automation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Increasing attention has been paid to remanufacturing which plays an important role in environmental protection and circular economy. Disassembly is a key operation in remanufacturing, repair, and recycling. Several robotic disassembly developments have shown that the use of robots in disassembly is feasible; however, the programming of robots is usually complex, schedule-based, and time-consuming. Recent research about self-learning robotics and human-robot collaboration have created an opportunity for schedule-free robotics, in which various machine learning and deep learning techniques have been developed. This paper attempts to review the development of self-learning robots with applications in robotic disassembly and remanufacturing. Key algorithms, designs, control methods, and future research directions have been highlighted and analysed. This review paper serves as a useful resource for researchers in the areas of robotics, smart remanufacturing, and disassembly automation.

Original languageEnglish
Title of host publication2022 27th International Conference on Automation and Computing (ICAC)
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781665498074
ISBN (Print)9781665498081 (PoD)
DOIs
Publication statusPublished - 10 Oct 2022
Event27th International Conference on Automation and Computing, ICAC 2022 - Bristol, United Kingdom
Duration: 1 Sept 20223 Sept 2022

Publication series

NameInternational Conference on Automation and Computing (ICAC)

Conference

Conference27th International Conference on Automation and Computing, ICAC 2022
Country/TerritoryUnited Kingdom
CityBristol
Period1/09/223/09/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Disassembly
  • Learning Methods
  • Reinforcement Learning (RL)
  • Robotics
  • Self-Learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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