Real-time hierarchical GPS aided visual SLAM on urban environments
Real-time hierarchical GPS aided visual SLAM on urban environments
复制标题
城市环境中的实时分层 GPS 辅助视觉 SLAM
DOI：
10.1007/978-3-642-04772-5_43
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
M. E. L. Guillén
中科院分区：
文献类型：
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作者：
D. Schleicher;L. Bergasa;M. Ocaña;R. Barea;M. E. L. Guillén
在本文中，我们提出了一种新的实时分层（拓扑/度量）视觉SLAM系统，专注于在大规模的室外城市环境中的车辆定位。它完全基于低成本广角立体摄像机和低成本GPS提供的视觉信息。我们的方法将整个地图划分为由所谓的指纹（参考姿势）识别的局部子地图。在子地图层（低层SLAM），自然地标和车辆位置/方向的3D顺序映射使用自顶向下的贝叶斯方法来建模的动态行为。增加了一个基于参考位姿的更高拓扑级别（高级SLAM），以减少全局累积漂移，保持实时约束。采用这种分层策略，我们保持局部一致性的度量子地图，通过扩展卡尔曼滤波器，和全局一致性，通过使用拓扑图和多级松弛（MLR）算法。全球定位系统的测量在两个层面上都得到了整合，从而改进了全球估计。不同的大规模城市环境的一些实验结果，显示出几乎恒定的处理时间。
In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by both a low-cost wide-angle stereo camera and a low-cost GPS. Our approach divides the whole map into local sub-maps identified by the so-called fingerprint (reference poses). At the sub-map level (low level SLAM), 3D sequential mapping of natural landmarks and the vehicle location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (high level SLAM) based on references poses has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. GPS measurements are integrated at both levels, improving global estimation. Some experimental results for different large-scale urban environments are presented, showing an almost constant processing time.