Classification-design-optimization integrated picking robots: a review

Jingyang Xiang, Lianguo Wang, Li Li, Kee Hung Lai, Wei Cai

Research output: Journal article publicationReview articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Robot technology is considered one of the most promising technologies to achieve intelligent production, with picking robots being the most common type. Picking robots are highly integrated mechatronic systems, which autonomously complete tasks including picking, carrying, and sorting. The application of picking robots enhances the efficiency of production across various environments. In this paper, a classification-design-optimization-application integrated framework of picking robots is addressed, contributing to theoretical research and application of picking robots. Classification of picking robot is established and analyzed considering the differences of overall form and end-effector to guide the development of research strategies and approaches of picking robot. Design of picking robot is described from different aspects of the target, structure, monitoring, and control design. Additionally, the commonly used optimization methods for picking robots, including structural parameters, kinematics and dynamics, and energy consumption, are discussed. Finally, the application of picking robots under different environments is expounded, and the challenges and prospects of picking robots are highlighted. This study could present theoretical support and application measures for picking robot study and technology development.

Original languageEnglish
JournalJournal of Intelligent Manufacturing
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • Classification
  • Design
  • End-effector
  • Optimization
  • Picking robot
  • Recognition and localization

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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