Abstract: An improved point-line vision inertial measurement algorithm(PL-VIO) is proposed to solve the problem of numerous inertial measurement and visual track identification and imprecise image pose and edge accuracy in map object pose recognition.In the front end of vision,the sub-pixel edge extraction method is used to iterate and improve the accuracy of image edge corners,and the edge constraints are applied to the extracted corners to prevent sub-pixel edge detection from crossing the boundary.In order to improve the extraction accuracy and reduce the repeated extraction of line features at the visual backend,the line features and point features extracted by LSD are extracted and optimized.After SFM,the extracted line features are combined and redundant lines are deleted.Experiments are carried out using EuRoc data set based on ROS platform,and the obtained experimental data are imported into Evo.Evo is used to analyze and plot the experimental data,and the error parameters are evaluated.The overall reduction of error parameters in the experimental results verified the superiority and accuracy of the improved PL-VIO algorithm.

Key words: Point-line vision inertial range method, Edge extraction, Point and line features, ROS robot simulation platform, Line mergin