| 基于双目强约束的直接稀疏视觉里程计 |
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| 引用本文： | 叶培楚,李东,章云.基于双目强约束的直接稀疏视觉里程计[J].广东工业大学学报,2021,38(4):65-70. |
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| 作者姓名： | 叶培楚 李东 章云 |
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| 作者单位： | 广东工业大学 自动化学院，广东 广州 510006 |
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| 基金项目： | 广东省自然科学基金资助项目(2021A1515011867) |
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| 摘 要： | 为了提高双目直接稀疏里程计(Stereo Direct Sparse Odometry, Stereo DSO)的定位速度和精度, 使得移动机器人可以更有效地执行任务, 提出了一种基于双目强约束的直接稀疏视觉里程计系统。基于直接法的即时定位与地图构建(Simultaneous Localization and Mapping, SLAM)系统直接对图像像素构建光度误差优化函数, 无需提取特征点, 克服了基于特征点法的SLAM系统在弱纹理场景下不鲁棒的缺陷, 并且在前端跟踪阶段效率更高。提出一种快速、准确的双目初始化方法, 结合三角化不确定性为不同类型的点赋予不同的深度范围, 加速深度滤波器的收敛。同时, 在运动估计阶段引入双目约束, 使得该系统在绝对尺度上的定位更加准确。通过在公开的KITTI数据集11个序列上进行实验, 实验结果表明所提出的算法在定位精度上明显优于同样采用直接法的Stereo Large Scale Direct SLAM(LSD-SLAM2)和Stereo DSO, 并达到与基于特征点法的ORB-SLAM3相近的水平, 为直接法SLAM提供一种更优的定位方案。
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| 关 键 词： | 视觉里程计 直接法 移动机器人 SLAM |
| 收稿时间： | 2020-10-16 |
Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints |
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| Ye Pei-chu,Li Dong,Zhang Yun.Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints[J].Journal of Guangdong University of Technology,2021,38(4):65-70. |
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| Authors: | Ye Pei-chu Li Dong Zhang Yun |
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| Affiliation: | School of Automation, Guangdong University of Technology, Guangzhou 510006, China |
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| Abstract: | A new direct SLAM (Simultaneous Localization And Mapping) system with enhanced stereo-camera constrains based on Stereo Direct Sparse Odometry (Stereo DSO) is presented. As a direct SLAM method, any image pixel with sufficient intensity gradient can be utilized, which makes it robust even in featureless areas. Two-stage checking combining SAD (Sum of Absolute Differences) with NCC (Normalized Cross Correlation) matching method is used for stereo matching and triangulated uncertainty concerned to accelerate the convergence of depth filters. To estimate the accurate scale of the environment, static stereo constrains are added to the tracking module. Our evaluation on KITTI demonstrates that the proposed system achieves the better performance than the state of the art direct SLAM systems such as LSD-SLAM2 and Stereo DSO, and achieves the comparable performance with ORB-SLAM3 which is the state of the art feature SLAM. The proposal provides mobile robots with a new direct SLAM system to explore the environment more precisely and robustly. |
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| Keywords: | visual odometer direct method mobile robot simultaneous localization and mapping(SLAM) |
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