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Grid-based localization and local mapping with moving object detection and tracking

机译:基于网格的本地化和本地映射以及运动对象的检测和跟踪

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摘要

We present a real-time algorithm for simultaneous localization and local mapping (local SLAM) with detection and tracking of moving objects (DATMO) in dynamic outdoor environments from a moving vehicle equipped with a laser scanner, short-range radars and odometry. To correct the vehicle odometry we introduce a new fast implementation of incremental scan matching method that can work reliably in dynamic outdoor environments. After obtaining a good vehicle localization, the map surrounding of the vehicle is updated incrementally and moving objects are detected without a priori knowledge of the targets. Detected moving objects are finally tracked by a Multiple Hypothesis Tracker (MHT) coupled with an adaptive Interacting Multiple Model (IMM) filter. The experimental results on datasets collected from different scenarios such as: urban streets, country roads and highways demonstrate the efficiency of the proposed algorithm.
机译:我们提出了一种实时算法,用于同时进行定位和局部地图绘制(local SLAM),并在动态户外环境中从装有激光扫描仪,短程雷达和里程表的移动车辆中检测和跟踪移动物体(DATMO)。为了纠正车辆里程表,我们引入了增量扫描匹配方法的新快速实现方法,该方法可以在动态室外环境中可靠地工作。在获得良好的车辆定位之后,车辆周围的地图将逐步更新,并且无需事先知道目标即可检测到移动物体。最后,通过多重假设跟踪器(MHT)和自适应交互多模型(IMM)过滤器对检测到的运动对象进行跟踪。在从不同场景(例如城市街道,乡村道路和高速公路)收集的数据集上的实验结果证明了该算法的有效性。

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