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Laserscanner Innovations for Detection of Obstacles and Road

机译:用于障碍物和道路检测的Laserscanner创新

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摘要

This paper presents innovations for detection of obstacles and road using a Multilayer Laserscanner. The classification of pedestrians and other road users require robust object tracking algorithms. Their reliability strongly depends on a precise ego-motion compensation. A new method of ego-motion estimation based on relative velocities of tracked objects will be introduced. This method operates especially under undefined driving conditions, such as skidding of the ego vehicle, where algorithms based on the vehicle's INS data fail. High performance object tracking and classification algorithms for real-time data processing will be introduced. Especially the results of a new pedestrian recognition technique will be presented. Methods for road detection and road type classification based on Laserscanner data will be explained in a separated chapter. The fusion of road detection and object recognition will enable a better interpretation of driving situations.
机译:本文介绍了使用多层激光扫描仪检测障碍物和道路的创新技术。行人和其他道路使用者的分类需要强大的对象跟踪算法。它们的可靠性在很大程度上取决于精确的自我运动补偿。介绍了一种基于被跟踪物体相对速度的自我运动估计新方法。该方法尤其在不确定的驾驶条件下运行,例如在自我车辆的打滑情况下,其中基于车辆INS数据的算法将失败。将介绍用于实时数据处理的高性能对象跟踪和分类算法。特别是将介绍一种新的行人识别技术的结果。将在单独的章节中说明基于Laserscanner数据的道路检测和道路类型分类的方法。道路检测和物体识别的融合将使驾驶情况得到更好的解释。

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