基于多传感器数据融合的智能小车避障的研究  

Study on obstacle avoidance of intelligent machine based on multi-sensor data fusion

作　　者：刘金强[1] 聂诗良[1] 潘泽友[2] 冯聪杰[1] 

机构地区：[1]西南科技大学信息工程学院,四川绵阳621010 [2]中国工程物理研究院计算机应用研究所,四川绵阳621900

出　　处：《传感器与微系统》2010年第2期66-68,共3页Transducer and Microsystem Technologies

摘　　要：针对智能小车避障问题,提出了一种将模糊逻辑和神经网络相结合的融合方法—Takagi-Sugeno(T-S)模糊神经网络方法。基于此方法的数据融合算法应用在智能小车避障运动中,采用多只超声波传感器和红外线传感器探测障碍物的距离和方向,采集的各种数据利用T-S模糊神经网络进行融合。通过实验仿真表明:此方法能够使智能小车对障碍物的灵活避障和导航行进。Aimed at the problem of obstacle avoidance of intelligent machine, a novel approach of muhi-sensor information fusion based on neural networks and fuzzy logic, i. e. T-S fuzzy neural networks method is presented. The method based on data fusion algorithm is used in intelligent machine obstacle-avoiding movement, several ultrasonic sensors and infrared sensors are used for detecting distance and direction of the obstacle. All kinds of collected data are integrated by the T-S fuzzy neural networks. The simulation experiment indicates that the method which is used in avoiding the obstacle and navigating of intelligent machine is flexible.

关 键 词：多传感器数据融合 避障 模糊神经网络 智能小车 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]