机器人2017，Vol.39Issue(5)：638-651,14.DOI:10.13973/j.cnki.robot.2017.0638
基于多激光雷达与组合特征的非结构化环境负障碍物检测
Negative Obstacle Detection in Unstructured Environment Based on Multiple LiDARs and Compositional Features
摘要
Abstract
For negative obstacle detection of autonomous land vehicle (ALV) in unstructured environment, a method based on multiple LiDARs and compositional features is proposed. Firstly, a multi-LiDAR installation manner with complementary ability is proposed. Secondly, two methods are presented: a negative obstacle feature point pair detection method with 64-beam LiDAR based on local convexity in amplitude direction and local dense features at up-side of a ditch, and a negative obstacle feature point pair detection method with 32-beam LiDAR based on range jump in radial direction and local dense features at up-side of a ditch. From the view of spatial and temporal fusion of the negative obstacle, a Bayesian rule is adopted to fuse the feature point pairs from multiple sensors and multiple frames. Then the DBSCAN (density-based spatial clustering of applications with noise) algorithm is applied to clustering and filtering the feature point pairs after fusion. Finally, the data are discretized to extract negative obstacle grid. The experimental results show that the proposed method obtains a good performance for detecting negative obstacles in unstructured environment.关键词
负障碍/激光雷达/非结构化环境/自主式地面车辆Key words
negative obstacle/LiDAR/unstructured environment/ALV (autonomous land vehicle)分类
信息技术与安全科学引用本文复制引用
刘家银,唐振民,王安东,石朝侠..基于多激光雷达与组合特征的非结构化环境负障碍物检测[J].机器人,2017,39(5):638-651,14.基金项目
国家自然科学基金(61473154,61371040,61373063,91420201) （61473154,61371040,61373063,91420201）
国家装备预研领域基金(6140312010101). （6140312010101）
