| 神经网络的多传感器数据融合基于新算法在障碍物识别中的应用 |
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| 引用本文： | 朱晓芸,杨建刚,何志钧. 神经网络的多传感器数据融合基于新算法在障碍物识别中的应用[J]. 机器人, 1997, 0(3) |
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| 作者姓名： | 朱晓芸 杨建刚 何志钧 |
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| 作者单位： | 浙江大学计算机科学与工程学系 |
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| 摘 要： | 本文提出了一种用于自主式移动机器人的障碍物类型识别的数据融合新方法，有两种不同的神经网络——小脑模型联接控制器（ＣＭＡＣ）和多层前向网分别对来自ＣＣＤ摄象机的二维图象和来自超声测距系统的距离信息进行数据融合，而这两种神经网络事先都用围绕障碍物采集的数据集进行过离线训练．为了验证该系统的有效性，我们构造了一系列的仿真实验．实验结果表明，一台个人计算机就能实时地识别出障碍物的类型．
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| 关 键 词： | 传感器，数据融合，神经网络，移动式机器人 |
APPLICATION OF A NEW ANN BASED MULTI SENSOR DATA FUSION ALGORITHM TO OBSTACLE CATEGORY IDENTIFICATION |
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| ZHU Xiaoyun YANG Jiangang HE Zhijun. APPLICATION OF A NEW ANN BASED MULTI SENSOR DATA FUSION ALGORITHM TO OBSTACLE CATEGORY IDENTIFICATION[J]. Robot, 1997, 0(3) |
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| Authors: | ZHU Xiaoyun YANG Jiangang HE Zhijun |
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| Abstract: | This paper presents a new multi sensor data fusion algorithm to identify obstacle categories for an autonomous mobile robot. The 2D image from CCD camera and the range information from an ultrasonic ranging system are fused by two kinds of neural networks-a Cerebella Model Articulation Controller (CMAC) and a multi layer feedforward network. They are off line trained by a set of data which are collected around the obstacles. To show the effectiveness of the proposed system, a series of simulation experiments were conducted. The results show that the category of an obstacle can be identified in real time using a personal computer. |
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| Keywords: | Sensor data fusion nerual network mobile robot |
| 本文献已被 CNKI 等数据库收录！ |
