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Real-time motion planning for a mobile robot in an unknown environment using a neuro-fuzzy based approach

机译:使用基于神经模糊的方法的未知环境中的移动机器人的实时运动规划

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A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.
机译:提出了一种神经模糊网络的未知环境中的机器人运动方法。为了控制在未知环境中的机器人运动,机器人的行为被分类为移动到目标并避免障碍物。然后,根据机器人的动态和机器人的行为特征在未知的环境中,引入了模糊的控制规则来控制机器人运动。最后,设计了6层神经模糊网络,旨在合并机器人感测到机器人运动控制。在培训之后,网络可用于机器人运动控制。仿真结果表明,该方法对于未知环境中的机器人运动控制是有效的。

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