无人驾驶车辆单目视觉里程计快速位姿估计

针对传统的单目视觉里程计位姿估计算法无法满足无人驾驶车辆实时定位需求的问题,提出了一种基于基础矩阵性质改进的快速位姿估计算法。通过优化基础矩阵的计算过程来提高算法的实时性,首先得到含有8个未知参数的基础矩阵,然后利用特征匹配点对来求解基础矩阵。通过仿真实验对算法的效率和精度进行了分析,并将其与现有的算法进行了对比。实验结果表明,在不降低运动估计结果精度的前提下,优化后的位姿估计算法的运行速度可以在传统算法的基础上提高近4倍。研究对视觉里程计在无人驾驶车辆上的实时应用具有一定的参考价值。

A fast monocular visual odometry pose estimation method for self-driving vehicles

Aiming at the problem that the traditional pose estimation algorithm of monocular odometry cannot meet the needs of real-time localization of self-driving vehicles, a fast pose estimation algorithm based on the improvement of the fundamental matrix is proposed. By optimizing the calculation process of the fundamental matrix, the real-time performance of the algorithm is improved. The fundamental matrix with 8 unknown parameters is first obtained, and then the feature matching point pairs are used to solve the fundamental matrix. Through simulation experiments, the efficiency and accuracy of the algorithm are analyzed, and then it is compared with the existing algorithms. Experimental results show that the proposed algorithm can improve the speed of motion estimation by 4 times without the reduction of the accuracy of motion estimation. The study provides certain reference value to the real time application of the visual odometry of self-driving vehicles.