Robotic disassembly for end-of-life products focusing on task and motion planning: A comprehensive survey

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Abstract

The rise of mass production and the resulting accumulation of end-of-life (EoL) products present a growing challenge in waste management and highlight the need for efficient resource recovery. In response to this challenge, robotic disassembly has emerged as a vital tool for the circular economy. Combining accuracy, adaptability, and the potential for handling hazardous materials offers a sustainable solution for dismantling complex EoL objects. This comprehensive survey delves into the motivations for robotic disassembly and the pivotal role of task and motion planning (TAMP) in optimising disassembly processes. It analyses the evolution of disassembly strategies, from conventional methods to those driven by cutting-edge artificial intelligence (AI) techniques, for the future of waste management. Additionally, the survey explores several case study applications, focusing on the disassembly of EV lithium-ion batteries. It highlights how TAMP and AI integration can bolster adaptability, safety, and informed decision-making within real-world disassembly challenges. Finally, the review examines promising future research directions in robotics that hold the potential to advance further improvement in robotic disassembly to increase sustainability and the responsible management of EoL products.

Original languageEnglish
Pages (from-to)483-524
Number of pages42
JournalJournal of Manufacturing Systems
Volume77
Early online date19 Oct 2024
DOIs
Publication statusPublished - Dec 2024

Bibliographical note

Copyright © 2024 The Authors. Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers. This is an open access article under the CC BY
license ( https://creativecommons.org/licenses/by/4.0/ ).

Funding

This work was supported by the “Research and Development of a Highly Automated and Safe Streamlined Process for Increased Lithium-ion Battery Repurposing and Recycling (REBELION) ” project, supported by Grant 101104241. We extend our appreciation to the Manufacturing Technology Centre (MTC), particularly to Karol Janik and Thomas Legleu.

Keywords

  • Circular Economy
  • Electric vehicles
  • Lithium-ion batteries
  • Recycling
  • Robotic disassembly
  • Task and motion planning

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