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The design of an autonomous parallel parking neuro-fuzzy controller for a car-like mobile robot

机译:用于汽车样移动机器人的自主并行停车神经模糊控制器的设计

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The paper presents an autonomous parallel parking neuro-fuzzy controller for a car-like mobile robot. Three ultrasonic sensors are mounted in the front left corner of the car to obtain the parking environmental information and a compass sensor is mounted in the centre position of the car to measure the posture of the car. Through the proposed mechanism, one of the three ultrasonic sensors and the compass sensor are used to decide on the turning angle. Fifth-order polynomial reference paths starting from three different points to the same goal point have been used to generate the training data set. The fuzzy controller has been identified by subtractive clustering algorithm and trained by the adaptive neuro-fuzzy inference systems. The simulation results show that the proposed approach can successfully determine the motion direction at each sampling time without knowing the parking lot dimension, based on the direct sensors readings.
机译:本文介绍了一个自动并行停放的汽车般的移动机器人的神经模糊控制器。三个超声波传感器安装在汽车的前左角,以获得停车环境信息,并将罗盘传感器安装在汽车的中心位置,以测量汽车的姿势。通过所提出的机制,三种超声波传感器之一和罗盘传感器用于决定转动角度。从三个不同点开始到相同目标点的第五阶多项式参考路径已被用于生成训练数据集。通过减法聚类算法识别模糊控制器,由自适应神经模糊推理系统训练。仿真结果表明,基于直接传感器读数,所提出的方法可以在每个采样时间成功确定每个采样时间的运动方向。

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