[1]诸葛程晨,许劲松,唐振民.基于支持向量机的局部路径规划算法[J].哈尔滨工程大学学报,2019,40(02):323-330.[doi:10.11990/jheu.201708085]
 ZHUGE Chengchen,XU Jinsong,TANG Zhenmin.A local path planning method based on support vector machine[J].hebgcdxxb,2019,40(02):323-330.[doi:10.11990/jheu.201708085]
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基于支持向量机的局部路径规划算法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2019年02期
页码:
323-330
栏目:
出版日期:
2019-02-05

文章信息/Info

Title:
A local path planning method based on support vector machine
作者:
诸葛程晨1 许劲松2 唐振民1
1. 南京理工大学 计算机科学与技术学院, 江苏 南京 210094;
2. 悉尼科技大学 大数据中心, 新南威尔士 悉尼 2007
Author(s):
ZHUGE Chengchen1 XU Jinsong2 TANG Zhenmin1
1. School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing 210094, China;
2. School of Electrical and Data Engineering Sydney University of Technology, Sydney 2007, Australia
关键词:
非结构化道路地面自主车辆路径规划支持向量机RANSAC算法局部路径栅格地图
分类号:
TP249
DOI:
10.11990/jheu.201708085
文献标志码:
A
摘要:
针对在非结构化道路环境下地面自主车辆的路径规划问题,本文提出了一种基于64激光雷达以及支持向量机的局部路径规划算法。利用非线性支持向量机分类器在栅格地图上提取出安全的路径;并在多帧投影数据上使用RANSAC算法提取出路径,并使用三次多项式进行描述,从而计算出道路曲率;结合地面自主车辆自身状态在RANSAC路径上选取控制点,并使用贝塞尔曲线拟合出最终路径。该算法能够有效地从局部栅格地图中提取道路,以弥补基于视觉的道路检测算法在受到恶劣光照、天气影响时的不足。通过实车试验验证了所提出的方法的有效性和正确性。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-08-28。
基金项目:国家自然科学基金项目(61403202,61371040);中国博士后科学基金面上项目(2014M561654);高等学校博士学科点专项科研基金项目(20133219120035);核高基国家重大专项(2015ZX01041101).
作者简介:诸葛程晨(1986-),男,博士研究生;唐振民(1961-),男,教授,博士生导师.
通讯作者:诸葛程晨,E-mail:zgccmax@163.com
更新日期/Last Update: 2019-01-30