机器人自动轴孔装配研究进展

徐德; 秦方博

doi:10.11959/j.issn.2096-6652.202223

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机器人自动轴孔装配研究进展

专题：自主智能体灵巧精准操作学习 | 更新时间：2024-06-05

- 机器人自动轴孔装配研究进展
- Research development on automated robotic peg-in-hole assembly
- 智能科学与技术学报 2022年4卷第2期页码：200-211
- 作者机构：
- 作者简介：
  
  [ "徐德（1965−），男，博士，中国科学院自动化研究所研究员，主要研究方向为机器人视觉测量、视觉控制、智能控制、视觉定位、显微视觉、微装配、技能学习" ]
  [ "秦方博（1992−），男，博士，中国科学院自动化研究所副研究员，主要研究方向为机器人视觉感知、精密装配机器人、植入手术机器人、深度学习" ]
- 基金信息：
  
  科技创新2030—“新一代人工智能”重大项目;The National Key Research and Development Program of China(2018AAA0103005);国家自然科学基金资助项目;The National Natural Science Foundation of China(61873266);国家自然科学基金资助项目;The National Natural Science Foundation of China(62103413)
- DOI：10.11959/j.issn.2096-6652.202223
  中图分类号： TP242.6
- 网络出版日期：2022-06，
  
  纸质出版日期：2022-06-15
- 稿件说明：
移动端阅览
徐德, 秦方博. 机器人自动轴孔装配研究进展[J]. 智能科学与技术学报, 2022,4(2):200-211.

De XU, Fangbo QIN. Research development on automated robotic peg-in-hole assembly[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 200-211.
徐德, 秦方博. 机器人自动轴孔装配研究进展[J]. 智能科学与技术学报, 2022,4(2):200-211. DOI： 10.11959/j.issn.2096-6652.202223.

De XU, Fangbo QIN. Research development on automated robotic peg-in-hole assembly[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 200-211. DOI： 10.11959/j.issn.2096-6652.202223.

摘要

轴孔装配是加工制造业常见的一类操作任务。基于工业机器人研究轴孔自动装配，对于机器人在装配领域的应用具有重要价值。对于高精密和形状复杂的零件，高效可靠的轴孔装配仍然具有很大挑战性。基于此，从控制的角度对机器人自动轴孔装配进行了全面梳理。首先，介绍了机器人自动轴孔装配过程。然后，在对基于传统模型的装配控制进行论述的基础上，对新兴的基于学习的智能装配控制进行了讨论，重点阐述了模仿学习和强化学习在机器人自动装配中的应用。传统方法与人工智能方法的结合，将为机器人自动轴孔装配注入新的活力，将成为未来的重要发展趋势。

Abstract

Peg-in-hole assembly is a typical operation task in manufactory.The research of peg-in-hole assembly based on industrial robots is valuable for the application of robots in the automated assembly area.For the peg-in-hole components with high precision or complex shapes

the efficient and reliable assembly is still very challenging.The development of automated robotic peg-in-hole assembly of peg-in-hole was reviewed from the view of control.First

the process of robotic peg-in-hole assembly was introduced.Secondly

the assembly control methods based on the traditional models were described.The newly emerged intelligent assembly methods based on learning mechanism were discussed

especially the applications of imitation learning and reinforcement learning in the automated robotic assembly.The combination of the traditional methods and the artificial intelligent methods will provide new energy for the automated robotic assembly

which will be one of the important developing tendencies in future.

关键词

Keywords

references

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