广东工业大学学报2017，Vol.34Issue(6)：32-36,5.DOI:10.12052/gdutxb.170050
基于BA的改进视觉/惯性融合定位算法
An Improved Visual Odometry/SINS Integrated Localization Algorithm Based on BA
摘要
Abstract
The robot's self-localization is the key to realize navigation and intelligent.To deal with the accuracy of location problem of the flying robot in indoor environment,an improved visual odometry/SINS integrated localization algorithm based on BA is proposed.First,the proposed method combines the calculation of visual information by direct method with the angular velocity and acceleration information of inertial unit,and iterate using extended Kalman filter method,which enhances the robustness of the visual odometry.The estimation preciseness of feature points' depth information is improved with inverse depth method.Then bundle adjustment is used for local optimization.The experiment results show that the proposed algorithm has effectively improved the preciseness of robot-pose estimation.关键词
惯性单元/直接法/视觉里程计/光束平差Key words
inertial measuring unit (IMU)/direct methods/visual odometry/bundle adjustment分类
信息技术与安全科学引用本文复制引用
马晓东,曾碧,叶林锋..基于BA的改进视觉/惯性融合定位算法[J].广东工业大学学报,2017,34(6):32-36,5.基金项目
广东省产学研专项(2014B090904080) （2014B090904080）
广州市重点科技项目(201604020016) （201604020016）
东莞产学研合作成果转化项目(2015509109107) （2015509109107）
