微型机与应用Issue(19)：80-82,85,4.
基于贝叶斯网络和多传感器的障碍物识别系统
Obstacle recognition system based on Bayesian network and multi-sensor
张超 1李磊民2
作者信息
- 1. 西南科技大学 信息工程学院，四川 绵阳 621010
- 2. 西南科技大学 国防科技学院，四川 绵阳 621010
- 折叠
摘要
Abstract
Because of the obstacle information′s uncertainty, incompleteness and the short of Bayesian classifier that it is sensitive for incomplete information, the paper selects a Bayesian network classification scheme. When building the Bayesian network model, this program using Bayesian inference which can improve the adaptability of the Bayesian network. The classification system relies on a research institute unmanned vehicle project. Real-time information is obtained via laser radar and CCD sensor that provides data to the network model.关键词
无人车/贝叶斯网络/障碍物/分类Key words
unmanned vehicle/Bayesian network/obstacle/classification分类
计算机与自动化引用本文复制引用
张超,李磊民..基于贝叶斯网络和多传感器的障碍物识别系统[J].微型机与应用,2015,(19):80-82,85,4.
