KLT-VIO:Real-time Monocular Visual-Inertial Odometry  

作　　者：Yuhao Jin Hang Li Shoulin Yin 

机构地区：[1]Software College,Shenyang Normal University No.253,Huanghe North Street,Huanggu District,Shenyang,110034 China

出　　处：《IJLAI Transactions on Science and Engineering》2024年第1期8-16,共9页IJLAI科学与工程学报汇刊（英文）

摘　　要：This paper proposes a Visual-Inertial Odometry(VIO)algorithm that relies solely on monocular cameras and Inertial Measurement Units(IMU),capable of real-time self-position estimation for robots during movement.By integrating the optical flow method,the algorithm tracks both point and line features in images simultaneously,significantly reducing computational complexity and the matching time for line feature descriptors.Additionally,this paper advances the triangulation method for line features,using depth information from line segment endpoints to determine their Plcker coordinates in three-dimensional space.Tests on the EuRoC datasets show that the proposed algorithm outperforms PL-VIO in terms of processing speed per frame,with an approximate 5%to 10%improvement in both relative pose error(RPE)and absolute trajectory error(ATE).These results demonstrate that the proposed VIO algorithm is an efficient solution suitable for low-computing platforms requiring real-time localization and navigation.

关 键 词：Visual-inertial odometry Opticalflow Point features Line features Bundle adjustment 

分 类 号：TN9[电子电信—信息与通信工程]