基于模糊神经网络算法的智能轮椅沿墙走行为研究

为了解决移动机器人在户外自主导航移动过程中的局部路径规划问题,提出了一种更为实用的模糊神经网络算法来进行局部路径规划。利用多个声纳和一个摄像头来采集外部环境信息,使智能轮椅在移动过程中可以得到较全面的外部环境信息,使用模糊神经网络算法来对得到的环境信息进行融合,应用的神经网络模型为Takagi-Sugeno(T-S)型,通过融合的结果来控制轮椅的沿墙走行为。通过计算机仿真和实验,验证了该方法的可行性和有效性,轮椅沿墙行走的路径得到了优化。

Behavior of intelligent wheelchair along wall based on algorithm of fuzzy neural network

In order to solve the problem that the process of local path planning about the mobile robot,which autonomous navigation in outdoor.A more practical method of local path planning is presented,which is based on the algorithm of fuzzy neural network.Firstly the intelligent wheelchair has few numbers of sonar and a camera to collect external environmental information when it is moving.So,the intelligent wheelchair can get sufficient information on the external environment.Then the fuzzy neural network based on the Takagi-Sugeno(TS) mode is used to fuse the information of the environment.In the end,the result of the information fusion is used to control the wheelchair’s move.The simulation and experiment show that this method is feasibility and validity.And the path of the intelligent wheelchair is optimized.