大连理工大学学报2012，Vol.52Issue(1)：132-138,7.
无人驾驶车在越野环境中障碍身份识别
Obstacle identification in cross-country environment for unmanned ground vehicle
摘要
Abstract
Aiming at the problem of cross-country environment perception of unmanned ground vehicle,Dempster fusion rules are applied to identifying obstacle.Firstly,five kinds of representative features are selected based on CCD and laser sensor.Secondly,sensor data is transformed to evidence space,and the obstacle identification membership is computed by using fuzzy interpolative method,then correlation coefficient is obtained.Thirdly,according to obstacle identity and weight correlation,experimental formula is selected to compute basic probability assignment function.Finally,based on Dempster fusion rules,the ultimate basic probability assignment function is acquired,the identification and decision-making rules are set to determine obstacle classification.Test results show the good robustness and real-time property by using D-S theory to identify obstacle.关键词
无人驾驶车/环境感知/D-S证据理论/基本概率赋值函数Key words
unmanned ground vehicles/environment perception/D-S theory of evidence/basic probability assignment function分类
信息技术与安全科学引用本文复制引用
赵一兵,郭烈,张明恒,李琳辉..无人驾驶车在越野环境中障碍身份识别[J].大连理工大学学报,2012,52(1):132-138,7.基金项目
中国航天科技集团五院总体部资助项目 （）
