针对视觉里程计在弱纹理的道路环境下定位精度骤降的问题,提出一种双目视觉里程计优化算法。首先,通过提取局部特征平面,为立体匹配缺失的特征提供平面约束,增加有效立体特征的数量;其次,在特征追踪过程中,使用匀加速运动模型,提高特征追踪的数量和质量;最后,在位姿计算和优化过程中,使用考虑特征置信度的光束法平差算法来减少远距离特征引入的误差影响,提高算法的精度和稳健性。数据集实验和实际场景实验表明,该算法在占有极少计算资源的情况下对弱纹理环境下的定位精度有较明显的优化效果,在其他场景也具有较好的适应性。

To solve the problem that the accuracy of visual odometry was decreased in the weak texture environment, an optimization algorithm of binocular visual odometry is proposed. Firstly, the planar constraints are provided for the features without stereo matching by extracting the local feature plane, to increase the quantity of effective stereo features. Secondly, in feature tracking, the uniform acceleration motion model is used during feature tracking to increase the quantity and improve the quality of tracked features. Finally, in pose estimation and optimization, the bundle adjustment method which considers the feature confidence is adopted to reduce the influence of distant feature, and improve the accuracy and robustness of the algorithm. The experimental results based on the datasets and actual scene show that the proposed algorithm has obvious optimization effect on the positioning accuracy under weak texture environment with little computational resources, and has adaptability in other scenes.