ALIMC: 基于活动地标的众包室内制图方法

ALIMC: Activity Landmark-Based Indoor Mapping via Crowdsourcing

   室内地图是行人导航系统中不可或缺的，也是智能交通系统的重要要素。本文中，作者提出了一种ALIMC，即基于活动地标的众包室内制图系统。 ALIMC能够通过智能手机所收集的众包数据构建匿名建筑的室内地图，而不需要任何先验知识。ALIMC利用节点关系模型抽象的表达室内地图，其中路径通过边表示，路径的交点用节点表示，比如角落、电梯、楼梯等。当行人经过这些节点时会产生相关的活动，而智能手机能够捕获到这些活动。检测到活动之后，ALIMIC能够从众包数据中提取出活动地标并且将活动地标聚簇成不同的簇，每一个簇就作为室内地图的一个节点。然后ALIMC能够估计出所有节点之间的距离并将其记录在距离矩阵中。在距离矩阵基础上，ALIMC能够通过一种多维尺度技术(Multidimensional Scaling Technique）生成一种相对的室内地图。最后， ALIMC基于若干个参考点将相对室内地图转为城一种绝对地图。为了评估ALIMC，作者在办公楼中实现了ALIMC。实验结果表明，80%情况下室内制图的精度约为0.8-1.5米。

Abstract—Indoor maps are integral to pedestrian navigation systems, an essential element of intelligent transportation systems (ITS). In this paper, we propose ALIMC, i.e., Activity Landmark based Indoor Mapping system via Crowdsourcing. ALIMC can automatically construct indoor maps for anonymous buildings without any prior knowledge using crowdsourcing data collected by smartphones. ALIMC abstracts the indoor map using a link–node model in which the pathways are the links and the intersections of the pathways are the nodes, such as corners, elevators, and stairs. When passing through the nodes, pedestrians do the corresponding activities, which are detected by smartphones. After activity detection, ALIMC extracts the activity landmarks from the crowdsourcing data and clusters the activity landmarks into different clusters, each of which is treated as a node of the indoor map. ALIMC then estimates the relative distances between all the nodes and obtains a distance matrix. Based on the distance matrix, ALIMC generates a relative indoor map using the multidimensional scaling technique. Finally, ALIMC converts the relative indoor map into an absolute one based on several reference points. To evaluate ALIMC, we implement ALIMC in an office building. Experiment results show that the 80th percentile error of the mapping accuracy is about 0.8–1.5 m.

Zhou, B.; Li, Q.; Mao, Q.; Tu, W.; Zhang, X.; CHEN, L., "ALIMC: Activity Landmark-Based Indoor Mapping via Crowdsourcing," Intelligent Transportation Systems, IEEE Transactions on , vol.PP, no.99, pp.1,12
doi: 10.1109/TITS.2015.2423326
keywords: Turning; Indoor mapping; activity landmark; crowdsourcing; smartphone
URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7103327&isnumber=4358928