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Fuzzy Neural Network based RFID Positioning and Navigation Method for Mobile Robots

机译:基于模糊神经网络的移动机器人RFID定位导航方法

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This study proposes the Radio Frequency Identification (RFID) indoor positioning and navigation method based on fuzzy neural network. The proposed method is applied to a wheelchair home health care robot with wireless communication. One reader and four tags are used. Based on the Received Signal Strength Indication (RSSI) data, the position of the robot can be determined. Further, to overcome the measurement error problem due to environmental parameter variation, a Fuzzy Neural Network (FNN) is proposed to compensate the measurement data. The FNN automatically adjust the weight, the variance and the mean value to overcome effectively the environmental parameter variation. A back-propagation algorithm is developed to achieve self-learning. The successful experiment results show that the proposed system architecture and positioning system provide satisfactory accuracy and make home health care wheelchair robot positioning system available for navigation and guidance.
机译:该研究提出了一种基于模糊神经网络的射频识别室内定位导航方法。所提出的方法被应用于具有无线通信的轮椅家庭保健机器人。使用一个读取器和四个标签。根据接收信号强度指示(RSSI)数据,可以确定机器人的位置。此外,为了克服由于环境参数变化引起的测量误差问题,提出了模糊神经网络(FNN)来补偿测量数据。 FNN自动调整权重,方差和平均值,以有效克服环境参数的变化。开发了一种反向传播算法以实现自学习。成功的实验结果表明,所提出的系统架构和定位系统提供了令人满意的精度,并使家庭保健轮椅机器人定位系统可用于导航和制导。

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