南京航空航天大学学报2025，Vol.57Issue(3)：397-411,15.DOI:10.16356/j.1005-2615.2025.03.001
数据驱动下的机器人轴孔装配研究综述
Data-Driven Robotic Shaft-Hole Assembly:A Review
摘要
Abstract
Shaft-hole assembly,as a core manufacturing process,critically determines product precision and reliability through intelligent advancement.Traditional manual algorithms suffer from strong model dependency and insufficient adaptability,whereas data-driven methods exhibit promising generalization capabilities by implicitly learning response patterns from operational data.This paper systematically reviews data-driven shaft-hole assembly technologies,organizing advancements across three dimensions:Environmental perception,assembly control,and task curriculum design.It analyzes agent perception mechanisms,task comprehension-control interactions,and curriculum design impacts in shaft-hole assembly.Addressing current bottlenecks in dynamic response,robustness,and task understanding,the study proposes future research directions:Task-oriented low-cost perception systems,prior knowledge-enhanced data-driven decision frameworks,performance evaluation in unknown task spaces,and task comprehension-control strategies under human-robot collaboration.关键词
轴孔装配/数据驱动/任务理解/多模态感知/课程设计Key words
peg-in-hole assembly/data-driven/task comprehension/multimodal perception/curriculum design分类
信息技术与安全科学引用本文复制引用
王战玺,张邦海,李景德,罗子彦,郑晨..数据驱动下的机器人轴孔装配研究综述[J].南京航空航天大学学报,2025,57(3):397-411,15.基金项目
航空科学基金(2024Z072053001) （2024Z072053001）
陕西省重点研发计划项目(2023ZDLGY-40) （2023ZDLGY-40）
陕西省重点研发计划项目:(2022ZDLGY03-06). （2022ZDLGY03-06）
