一种基于多个多线激光雷达分区障碍物检测方法

本发明公开一种基于多个多线激光雷达分区障碍物检测方法,流程如下:接收三路激光雷达数据缓存和拼接,过滤无效点和畸变的点;分区体素下采样,根据不同的检测区域设置不同的像素;下采样完后进行数据集合并;基于渐进式形态学滤波算法进行地面拟合,检测出地面点;进行地面分割,分割出非地面点和地面点;基于欧几里得算法对非地面点云集合进行聚类,根据扫描距离的远近,设置不同的k-维树近邻搜索的搜索半径,进行障碍物检测;输出障碍物信息给融合层或者动态障碍物跟踪模块,包含障碍物的长度、宽度、高度和中心点信息。本发明实现目标物的高精度识别,保障每一帧障碍物检出时延小于40ms,检出率为98%。 The invention...

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Format Patent
LanguageChinese
Published 02.04.2024
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Summary:本发明公开一种基于多个多线激光雷达分区障碍物检测方法,流程如下:接收三路激光雷达数据缓存和拼接,过滤无效点和畸变的点;分区体素下采样,根据不同的检测区域设置不同的像素;下采样完后进行数据集合并;基于渐进式形态学滤波算法进行地面拟合,检测出地面点;进行地面分割,分割出非地面点和地面点;基于欧几里得算法对非地面点云集合进行聚类,根据扫描距离的远近,设置不同的k-维树近邻搜索的搜索半径,进行障碍物检测;输出障碍物信息给融合层或者动态障碍物跟踪模块,包含障碍物的长度、宽度、高度和中心点信息。本发明实现目标物的高精度识别,保障每一帧障碍物检出时延小于40ms,检出率为98%。 The invention discloses a partition obstacle detection method based on multiple multi-line laser radars. The method comprises the following steps: receiving three paths of laser radar data for cachingand splicing, and filtering invalid points and distorted points; carrying out subregion voxel downsampling, and setting different pixels according to different detection areas; performing data set merging after down-sampling; performing ground fitting based on a progressive morphological filtering algorithm, and detecting ground points; carrying out ground segmentation to obtain non-ground pointsand ground points; clustering the non-ground point cloud set based on an Euclidean algorithm, setting different search radiuses of k-dimen
Bibliography:Application Number: CN202010815034