摘要
针对未知被测曲面形貌的情况,提出一种基于机器人的智能自主三维扫描方法,在进行粗扫描快速获取大致轮廓后,引入KNN算法,利用局部曲率值重新规划细扫描路径,基于笛卡尔空间规划机器人运动轨迹,控制机器人完成扫描。经过仿真分析与实验,该方案能够有效捕捉曲面上的细微特征,并与手动扫描结果高度一致,验证了其在未知曲面三维检测中的准确性和高效性。
In view of the unknown surface topography,a robot-based intelligent autonomous 3D scanning method was proposed.After rough scanning to quickly obtain the rough outline,the KNN algorithm,in conjunction with local curvature values,was introduced to recalculate the fine scanning path,and robot motion trajectory was planned based on Cartesian space to control the robot to complete the scanning.Through simulation analysis and experiments,the scheme can effectively capture the fine features on the surface,and is highly consistent with the manual scanning results,which verifies its accuracy and high efficiency in the 3D detection of unknown surfaces.
作者
陈隋郁
刘维
钟淼
陆高琪
刘璐
CHEN Suiyu;LIU Wei;ZHONG Miao;LU Gaoqi;LIU Lu(College of Metrology Measurement and Instrument,China Jiliang University,Hangzhou 310018,China)
出处
《组合机床与自动化加工技术》
北大核心
2025年第5期27-32,共6页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家级大学生创新创业训练计划资助项目(202310356011)
国家自然科学基金青年项目(12202428)。
