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针对室外移动机器人的行驶特点 ,将车体模型划分为前轮转向模型、速度模型和位姿模型三个部分 .提出用模糊集合与神经网络相结合来建立车体前轮转向模型的方法 .首先将对前轮转向特性影响较大的行车速度模糊化 ,然后利用神经网络建立各模糊速度下的前轮转向模型 ,最后由逆模糊化过程求得模型的实际输出 .实验结果表明 ,该方法能较准确地反映车体的前轮转向特性并具有鲁棒性强和易于实现的特点
According to the driving characteristics of the outdoor mobile robot, the body model is divided into three parts: the front wheel steering model, the speed model and the pose model, and the method of combining the fuzzy set with the neural network to establish the front steering model of the vehicle body is proposed. The speed of front wheel steering will be greatly obscured, and then the front steering model of each speed will be established by neural network, and the actual output of the model will be obtained by the inverse fuzzification process.The experimental results show that this method can More accurately reflect the front steering characteristics of the body and has strong robustness and easy to implement features