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Visual servo control for dynamic hovering of an underwater biomimetic vehicle-manipulator system by neural network

机译:视觉仿生控制的神经网络水下仿生车辆操纵器系统的动态悬停

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This paper deals with the problem of dynamic hovering of a bio-inspired robot with undulatory fins. First, the mechanism and dynamic model of the underwater robot named RobCutt-II is briefly introduced. Next, an neural network visual servo control is presented to achieve hovering control. In particular, a dual-loop visual hovering control is designed. At first, we analyze the relationship between the image feature error and the direction of the controllable velocity. In the outer loop, a PID controller is used to calculate the current controllable velocity based on image feature error in real time. Meanwhile, the inverse model of undulatory fins is established using the neural network. The velocity error is hereby mapped to the control parameters of the undulatory fins of the RobCutt-II. The simulation results of dynamic hovering are provided to illustrate the validity of the proposed method.
机译:本文研究了具有波动鳍的生物启发式机器人的动态悬停问题。首先,简要介绍了名为RobCutt-II的水下机器人的机理和动力学模型。接下来,提出了一种神经网络视觉伺服控制来实现悬停控制。特别地,设计了双环视觉悬停控制。首先,我们分析了图像特征误差与可控速度方向之间的关系。在外循环中,PID控制器用于基于图像特征误差实时计算当前可控速度。同时,利用神经网络建立起伏鳍的逆模型。由此将速度误差映射到RobCutt-II的起伏散热片的控制参数。提供了动态悬停的仿真结果,说明了该方法的有效性。

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