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Lie Guo
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越野环境中无人驾驶车的障碍目标识别
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Indexed by:期刊论文

Date of Publication:2011-07-15

Journal:数据采集与处理

Included Journals:Scopus、PKU、ISTIC、CSCD

Volume:26

Issue:4

Page Number:442-446

ISSN No.:1004-9037

Key Words:D-S证据理论;无人驾驶车;隶属度;基本概率赋值函数

Abstract:针对无人驾驶车环境感知技术,基于D-S证据理论融合多传感器信息,旨在解决障碍物身份识别技术难点.基于CCD和激光传感器建立信息融合系统,并提取每种障碍物的5个特征证据,包括距离对比度特征、平行四边形特征、边缘形状特征、灰度纹理特征和颜色特征.再根据目标类型和环境加权系数选择经验公式,通过模糊插值法求取身份隶属度近似获得各特征对目标的相关系数构造基本概率赋值函数.最后制定Dempster组合规则,融合多传感器特征信息识别障碍身份.试验表明本文方法能够准确有效地获取基本概率赋值函数,D-S证据理论融合方法提高了障碍物身份识别的准确性和鲁棒性.

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Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

Gender:Male

Alma Mater:吉林大学

Degree:Doctoral Degree

School/Department:机械工程学院

Discipline:Vehicle Engineering. Vehicle Operation Engineering

Business Address:海涵楼417A

Contact Information:15524800674

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Open time:2017.2.20

The Last Update Time:2017.2.20


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