In order to solve the accuracy degradation problem of the point feature SLAM algorithm in low texture environments,a UAV binocular vision SLAM algorithm based on line feature constraints is proposed.Firstly,the observation of line features by using a binocular camera is divided into three situations,that is,a monocular camera observing in two frames,a binocular camera observing in two frames,and a binocular camera observing in one frame.Secondly,the residual block and Jacobian matrix in the three situations are calculated respectively.Finally,the line feature constraints proposed in this paper are used to improve the VINS-Fusion algorithm.The experiments are conducted on the EuRoC dataset,and the results show that the proposed algorithm exhibits good performance in over half scenarios of the dataset,and has a 13.2% improvement on average in positioning accuracy compared with the VINS-Fusion algorithm before improvement.