摘要
针对智能车自主视觉导航需要快速准确地获取自身位置的要求,提出了一种鲁棒、高效、精确的立体视觉定位方法.计算中采用直接P3P位姿估计方法和RANSAC算法进行匹配内点检测和初始运动参量估计,极大地提高了计算准确度.利用基于一般相机模型序列正交迭代算法的立体视觉定位运动参量非线性优化法对立体相机的最近N帧运动参量和结构参量进行快速在线优化,与集束调整法相比,该方法的优化速度有较大提高,且能保证全局收敛,鲁棒性高.室外真实实验结果表明:本文方法计算速度快,定位准确度高,鲁棒性强,能满足导航定位的高性能要求.
For the intelligent vehicle autonomous visual navigation need to get real-time, accurate, robust their own location information, a robust, efficient and accurate stereo visual localization algorithm is proposed. A new direct P3P pose estimation with RANSAC was proposed to obtain matching inliers and initial motion parameters and greatly improve accuracy. Then a new motion parameters optimization method was proposed based on sequence orthogonal iterative algorithm for general camera models. Recent N frames motion and structure parameters of stereo camera were rapidly optimized online. Compared with bundle adjustment, the speed and robust of the proposed method greatly enhanced, and the proposed method could attain global convergence. The outdoor real experiments show this method has high accuracy, good robustness and high computing speed in localization that can meet the high performance requirement of navigation localization.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2013年第12期1442-1447,共6页
Acta Photonica Sinica
基金
国家自然科学基金(Nos.61370173
60872057)
工业控制技术国家重点实验室开放课题(No.ICT1240)
湖州市自然科学基金(No.2011YZ07)
国家级大学生创新创业训练计划项目(No.201210347010)资助
关键词
视觉定位
序列正交迭代算法
运动估计
视觉导航
Visual localization
Sequence Visual navigation orthogonal iterative algorithm
Motion estimation
