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Polar Grid Based Robust Pedestrian Tracking with Indoor Mobile Robot using Multiple Hypothesis Tracking Algorithm

机译:基于极性网格的强大的行人跟踪,使用多假设跟踪算法使用多个假设跟踪算法

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Autonomous mobile robots manipulating in human environments with the information about where the service target is and in which direction the target is heading typically can improve their interaction behaviors. By providing the capability of tracking the target pedestrian in an appropriate manner, the robot can assist people in various ways under different environments. In this paper, a pedestrian tracking system for indoor single laser range finder mounted robot is presented. The polar occupancy grid based DATMO system critically increases the performance of pedestrian detection. The multiple hypothesis tracking algorithm (MHT) is chose to perform robust pedestrian tracking. The key contribution of paper is the combination of polar grid based DATMO system and MHT which enhances the reliability and robustness of the pedestrian tracking especially when the target moves in complex motion patterns. Several experimental results will be shown to demonstrate the benefits of the proposed idea.
机译:在人类环境中操纵的自主移动机器人,其中包含关于服务目标的信息以及目标是标题的方向的信息通常可以改善其交互行为。通过以适当的方式提供跟踪目标行人的能力,机器人可以在不同环境下以各种方式提供帮助人们。本文介绍了一个用于室内单激光测距仪安装机器人的行人跟踪系统。基于极性占用网格的Datmo系统批判性地提高了行人检测的性能。多个假设跟踪算法(MHT)被选择用于执行强大的行人跟踪。纸张的主要贡献是基于极性网格基于的DATMO系统和MHT的组合,其提高了行人跟踪的可靠性和鲁棒性,特别是当目标在复杂运动模式中移动时。将显示几种实验结果来证明提出的想法的好处。

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