Multisensor-Based Human Detection and Tracking for Mobile Service Robots
Multisensor-Based Human Detection and Tracking for Mobile Service Robots
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DOI：
10.1109/tsmcb.2008.2004050
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发表时间：
2009-02-01
影响因子：
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通讯作者：
Hu, Huosheng
中科院分区：
文献类型：
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作者：
Bellotto, Nicola;Hu, Huosheng
服务机器人的一个基本问题是人机交互。为了执行这样的任务并提供所需的服务，这些机器人需要检测和跟踪周围的人。在本文中，我们提出了一个解决方案，用于人体跟踪的移动的机器人，实现多传感器数据融合技术。该系统采用了一种新的算法，基于激光腿检测使用机载激光测距仪（LRF）。该方法是基于从激光扫描中提取的典型腿图案的识别，这也被证明是非常有区别的在杂乱的环境中。这些模式可用于定位静止和行走的人，即使当机器人移动。此外，使用机器人的摄像头检测面部，并使用无迹卡尔曼滤波器的顺序实现将信息融合到腿的位置。所提出的解决方案是可行的服务机器人与类似的设备配置，并已成功地实现了两个不同的移动的平台。几个实验说明了我们的方法的有效性，显示出强大的人体跟踪可以在复杂的室内环境中进行。
One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection using the onboard laser range finder (LRF). The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to also be very discriminative in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera, and the information is fused to the legs' position using a sequential implementation of unscented Kalman filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms. Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.