数据采集与处理2011，Vol.26Issue(4)：442-446,5.
越野环境中无人驾驶车的障碍目标识别
Obstacle Identification in Cross-Country Environment for Unmanned Ground Vehicles
赵一兵 1郭烈 1张明恒 1李琳辉1
作者信息
- 1. 大连理工大学工业装备结构分析国家重点实验室,大连,116024
- 折叠
摘要
Abstract
Autonomous navigation in cross-country environments presents many new challenges including obstacle perception for unmanned ground vehicle. A new method suitable for recognizing obstacle is proposed. The first step is to build the sensor fusion system by using sensors such as CCD and ladar, then to extract five different types of features, including distance contrast, parallelogram rate, edge-shape-factor, gray texture and HSV value. The experiment formula is selected according to the types of obstacle and weight efficiency to calculate basic probability assignment (BPA). The subordinatien to each event in identification framework is obtained by using the fuzzy interpolation. It is supposed that the subordination is equal to correlation coefficient in the formula. Finally, dempster rules are used to integrate sensors information and the obstacle is recognized based on the D-S theory of evidence. The test results indicate that the resolution of BPA is correct, thus improving the validity and robustness of cross-country environment perception based on the new method.关键词
D-S证据理论/无人驾驶车/隶属度/基本概率赋值函数Key words
D-S theory of evidence/unmanned ground vehicles/subordination/basic probability assessment分类
计算机与自动化引用本文复制引用
赵一兵,郭烈,张明恒,李琳辉..越野环境中无人驾驶车的障碍目标识别[J].数据采集与处理,2011,26(4):442-446,5.
