无人车基于双目视觉的同时定位与地图构建 | |
段华旭; 闫飞; 庄严; 卜春光 | |
刊名 | 华中科技大学学报(自然科学版) |
2015 | |
卷号 | 43期号:S1页码:319-323 |
关键词 | 双目视觉 闭环检测 同时定位与地图构建 拓扑图优化 无人驾驶车 |
ISSN号 | 1671-4512 |
其他题名 | Simultaneous localization and mapping for UGVs with binocular camera |
产权排序 | 2 |
中文摘要 | 研究了无人驾驶车面向校园环境的同时定位与地图构建问题.采用双目视觉系统进行立体视觉图像匹配,并以此为基础完成优化前的位姿拓扑地图构建;采用了一种基于ORB图像特征和BoW模型的闭环检测算法,并利用时间连续性约束和几何一致性约束来提升闭环匹配正确率.位姿拓扑地图的后端优化采用了高斯-牛顿优化方法,并且在迭代过程中充分考虑了系统信息矩阵的稀疏性.利用实验室自主研发的Smart-Cruiser无人驾驶车平台在校园环境进行了实验,结果验证了本文所提方法的有效性和实用性. |
英文摘要 | Simultaneous localization and mapping (SLAM) problem for unmanned ground vehicles (UGVs) in campus environments was investigated. A stereo image matching algorithm was deployed to perform consistent pose estimation so that an initial pose-graph model was constructed. A loop closure detection algorithm based on oriented FAST and Rotated BRIEF (ORB) feature matching and bag-of-words (BOW) model was utilized in our work, which can provide the constraints of temporal consistency and of geometrical consistency to improve the accuracy of loop closure. The back-end implementation for graph-based SLAM was used the Gaussian-Newton optimization method and the sparse characteristics of the system information matrix was fully utilized in the iterative procedure. The experiments were conducted on our self-developed UGV in DUT campus, and the results show the validity and robust performance of the proposed approach |
收录类别 | EI |
语种 | 中文 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/17148] |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | 段华旭,闫飞,庄严,等. 无人车基于双目视觉的同时定位与地图构建[J]. 华中科技大学学报(自然科学版),2015,43(S1):319-323. |
APA | 段华旭,闫飞,庄严,&卜春光.(2015).无人车基于双目视觉的同时定位与地图构建.华中科技大学学报(自然科学版),43(S1),319-323. |
MLA | 段华旭,et al."无人车基于双目视觉的同时定位与地图构建".华中科技大学学报(自然科学版) 43.S1(2015):319-323. |
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