机械科学与技术2025，Vol.44Issue(10)：1686-1695,10.DOI:10.13433/j.cnki.1003-8728.20230355
结合局部最优分割的无人机室内定位新方法
A New Method for Indoor Localization of Unmanned Aerial Vehicles Combined with Local Optimal Segmentation
摘要
Abstract
In order to realize the indoor precise positioning of UAV under the conditions of no radio frequency positioning equipment deployment and no GPS signal,proposed an improved local optimal segmentation method.First,calculate affine transformations to equalize image grid motion statistics,and maximize the local features through the Hessian matrix;Secondly,a grid reference unit is used to detect pixel group pairs,and an optimization function is introduced to increase the weight of the grid where the feature points are located.The highest membership degree is obtained by comparing it with the neighboring grid.By combining the Progressive Sampling Consistency(PROSAC)algorithm again,feature point pairs with lower confidence are eliminated through threshold setting.Finally,the Decoupling Rotation Translation(DRT)strategy is adopted to complete the Inertial Measurement Unit(IMU)initialization pre integration and solve the spatial pose sequence.Set up flight experiments under weak lighting,complex textures,and viewpoint transformation conditions;Analysis of flight logs shows that the feature matching accuracy of multiple experiments is above 97%,and the running time is only 46%～72%of that of other combination algorithms.The indoor positioning accuracy of drones reaches 0.02 m,and the matching effect is good in a comprehensive environment.It solves the problems of long feature matching time,low accuracy,and inaccurate matching results,and the positioning is accurate,which has high application and reference value.关键词
无人机/网格运动统计/局部分割/误匹配剔除/栅格匹配/室内定位Key words
UAV/grid motion statistics/local segmentation/mismatch elimination/grid matching/indoor positioning分类
信息技术与安全科学引用本文复制引用
贺勇,余江涛,邓婷..结合局部最优分割的无人机室内定位新方法[J].机械科学与技术,2025,44(10):1686-1695,10.基金项目
长沙理工大学校企合作基金项目(30404022264) （30404022264）
