Indoor Navigation Using Adaptive Neuro Fuzzy Controller for Servant Robot

W. Budiharto, A. Jazidie, D. Purwanto
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引用次数: 23

Abstract

We present our ongoing work on the development of Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for humanoid servant robot designed for navigation based on vision. In this method, black line on the landmark used as a track for robot’s navigation using webcam as line sensor. We proposed architecture of ANFIS controller for servant robot based on mapping method, 3 input and 3 output applied to the controller. Only 45 training data used for navigation and best error starting at epoch 62. Each of the components are described in the paper and experimental results are presented. Humanoid servant robot also equipped with 4DOF arm robot, face recognition and text to speech processor. In order to demonstrate and measure the usefulness of such technologies for human-robot interaction, all components have been integrated and have been used for a servant robot named Srikandi I. Based on experiments, ANFIS controller successfully implemented as controller for robot’s navigation.
基于自适应神经模糊控制器的仆人机器人室内导航
本文介绍了基于视觉导航的类人服务型机器人自适应神经模糊推理系统(ANFIS)控制器的开发。该方法采用网络摄像头作为线传感器,将地标上的黑线作为机器人导航的轨迹。提出了基于映射法的佣人机器人ANFIS控制器体系结构,控制器采用三输入三输出。只有45个训练数据用于导航,最佳误差从epoch 62开始。文中对各组成部分进行了描述,并给出了实验结果。人形仆人机器人还配备了四自由度手臂机器人、人脸识别和文字转语音处理器。为了证明和衡量这些技术对人机交互的有用性,将所有组件集成并用于名为Srikandi i的仆人机器人。基于实验,ANFIS控制器成功地实现了机器人导航控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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