Research on Visual and Inertia Fusion Odometry Based on PROSAC Mismatched Culling Algorithm

Abstract

A method based on Progressive Sampling Consensus(PROSAC) combining Monocular visual and inertial navigation is proposed for localization, which focuses on solving the problem of self-positioning of low-cost devices in an unknown environment. This paper used the PROSAC algorithm, and the Inertial Measurement Unit (IMU) to calculate the relative motion distance of the camera by pre-integration to assist the positioning. the PROSAC mismatch culling algorithm is added to the visual inertial navigation odometry and compared its performance with traditional methods-VIORB, VINS in the EuRoC data sets. Proving the effectiveness of the method. The average error is 0.069m, which is 11.1% and 7.7% lower than the two algorithms.