全球定位系统2024，Vol.49Issue(3)：20-27,8.DOI:10.12265/j.gnss.2024024
改进视觉前端的视觉/惯导融合定位算法
Improved vision/inertial guidance fusion localization algorithm for vision front-end
摘要
Abstract
Aiming at the problem of high-precision positioning of mobile robot in Global Navigation Satellite System GNSS denied environment,An adaptive thresholding adaptive and generic accelerated segment test AGAST feature detection algorithm is proposed to improve the visual front-end of a vision/inertial guidance fusion localization system for mobile robots.The algorithm improves the visual odometry computation method by local histogram equalization and adaptive threshold detection,improves the quality of feature point extraction,and enhances the positioning accuracy and stability of visual odometry in complex environments.Visual odometry and inertial navigation system are fused based on factor graph optimization algorithm to realize high-precision positioning of mobile robot.The results show that,compared with the mainstream VINS-Mono algorithm,the proposed algorithm improves the positioning accuracy by 22.8％in the experiment of indoor data set and 59.7％in the experiment of outdoor data set,the proposed algorithm perform better than VINS-Mono algorithm in both two experiments and it can provide better positioning services for mobile robots.关键词
因子图优化(FGO)/自适应通用角点检测(AGAST)/视觉里程计(VO)/视觉/惯导融合Key words
factor graph optimization(FGO)/adaptive thresholds AGAST features(AGAST)/visual odometer(VO)/visual inertial fusion navigation分类
航空航天引用本文复制引用
李志政,聂志喜,王振杰,张远帆..改进视觉前端的视觉/惯导融合定位算法[J].全球定位系统,2024,49(3):20-27,8.基金项目
国家自然科学基金青年科学基金项目(42174020) （42174020）
国家自然科学基金面上项目(42104011) （42104011）
山东省自然科学基金青年基金(ZR2021QD069) （ZR2021QD069）
中国石油大学(华东)自主创新科研计划项目(理工科)青年基金(22CX06032A) （华东）
