基于多模态感知的机器人自适应装测技术研究

Research on Robot Adaptive Insertion and Measurement Technology Based on Multimodal Perception

  • 摘要: 本文系统研究了面向复杂、精密插拔场景的机器人自适应装测技术,旨在突破传统刚性自动化方案的局限性,实现制造过程的柔顺化与智能化进化。以“柔顺插拔”为核心,深入探讨了从机构设计、感知认知到控制决策的全链条关键技术。本文构建了一个基于视觉、力位控制等多模态信息融合的感知系统,实现了对接触状态、相对位姿误差的精准估计。并通过搭建智能化机器人工业场景实验平台和批量部署应用,对所提出的理论与方法进行了验证。本文所研究的技术能够显著提升机器人在高精度环境下插拔装配任务的成功率、效率和安全性,为智能制造系统的进化提供了新的技术路径与理论支撑。

     

    Abstract: This paper systematically investigates robot adaptive insertion and measurement technology for complex and precise plugging scenarios, aiming to overcome the limitations of traditional rigid automation solutions and achieve compliant and intelligent evolution in manufacturing processes. Focusing on "compliant insertion," it thoroughly explores key technologies across the full chain from mechanism design to perception-cognition and control-decision-making. A multimodal perception system integrating vision and force-position control is constructed to enable accurate estimation of contact states and relative pose errors. Through the establishment of an intelligent robotic industrial experimental platform and batch deployment applications, the proposed theories and methods are validated. The developed technology significantly enhances the success rate, efficiency, and safety of robotic plugging assembly tasks in high-precision environments, providing new technical pathways and theoretical foundations for the evolution of intelligent manufacturing.

     

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