基于D-S证据理论的障碍目标身份识别

以越野环境中典型的障碍物为识别目标,选用单目视觉与激光扫描仪建立融合系统,基于D-S证据理论融合多传感器信息,实现UGV对障碍目标的身份识别。首先将每个传感器的观测数据从观测空间变换到证据空间,对每种身份分配一个基本概率赋值;融合系统再根据Dempster组合规则计算各个命题组合后的概率赋值函数和相应的信任度区间,然后计算综合概率赋值函数和信任度区间;最后根据计算结果和决策规则进行障碍身份识别。试验表明:该方法优于利用单个特征识别障碍物身份,能大大提高系统对于障碍物的识别分类能力。

Obstacle identification based on dempster-shafer theory of evidence

Sensor data fusion system is composed from single color CCD and laser scanner.Based on Dempster-Shafer theory of evidence different sensor data are fused together to classify three kinds of typical obstacles.Firstly,sensor data are transformed to evidence which attributes to the obstacle`s characteristic.Since identity of the current obstacle is unknown,basic probability assignment is assigned to every classification.Then Dempster fusion rules are used to compute the ultimate BPA and Believe interval.Finall...