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March 7, 2026Chinese Journal of Mechanical Engineering3 citationsOpen Access

Recent progress and challenges of key technologies in robotic assembly

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LQLonghui Qin

Key Points

  • The aim is to assess recent progress and challenges in robotic assembly technologies.
  • Reviewed five key technologies: perception, end-effectors, control methods, learning methods, and performance evaluation.
  • Analyzed main works and characteristics in these fields.
  • Discussed challenges and future directions in robotic assembly.
  • Identified improvements in product quality and efficiency of robotic assembly.
  • Highlighted challenges like precise perception and error recovery.
  • Outlined future research areas in collaborative robotics.

Abstract

How to substitute the human operator with a robot in various assembly tasks has to be taken into full consideration in intelligent manufacturing. Autonomous robotic assembly not only brings with high working efficiency, better product quality and low labor cost, but also helps relieve the increasingly severe problem of population aging. However, numerous existing challenges still prevent its wide applications when a robot is assigned to finish general tasks in unstructured environment. In order to provide a fundamental understanding of the various problems involved in robotic assembly, this paper carries out a review on its recent progress and challenges with 5 key technologies focused on: perception, end-effectors, control methods, learning methods and performance evaluation. Main works in these fields are reviewed and their characteristics are analyzed while typical assembly scenarios are covered. The challenges and future directions in robotic assembly are also discussed on precise perception, robotic hand, error recovery and collaborative robot. In addition to providing a systematic summarization of the required key technologies, this work is aimed at motivating more potential researches in the community of robotics, artificial intelligence, and automation engineering.

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Cite This Study

Longhui Qin (2026) studied this question.

synapsesocial.com/papers/69abc2075af8044f7a4eb2c3https://doi.org/10.1016/j.cjme.2025.100032
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