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RBF神经网络在机器人视觉伺服控制中的应用
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江西省教育厅科技计划项目(GJJ13784)


Application of RBF Neural Networks in Visual Servo Control of Robots
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    摘要:

    传统的机器人视觉伺服控制是由系统雅可比矩阵的计算得到图像空间与机器人空间的非线性关系,这种方法不仅计算量大、系统结构复杂,而且对系统模型误差敏感。针对此问题,在分析视觉伺服数学模型的基础上,设计了RBF径向基函数神经网络来实现机器人视觉伺服系统手眼协调功能,从而简化控制算法。通过仿真实验证明所设计的径向基函数神经网络控制系统具有良好的目标定位效果和泛化能力,并且极大地缩短了视觉伺服所需时间,很好地保证了控制系统的实时性。

    Abstract:

    As realtime system Jacobian Matrix is needed in traditional visual servo control system of robot to calculate the nonlinear relationship between space of an image and of the robot, by this method the complexity of this system structure, large amount of calculation, and its sensitivity to system model error are expected to improve. Aimed at the problems, based on analysis of the mathematical model of the visual servo control system, a radial base function (RBF) neutral network controller was designed to realize visual servo control in imagebased robot with coordination function of eyes and hands, therefore control algorithm was simplified. Through following simulation experiment, it was proved that the designed control system of RBF neutral network having good target positioning effect and generalization capability. The time needed in the visual servo control is greatly shortened, and the control system in real time is very well ensured.

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郑立斌,王红梅,顾寄南,石长华,何辉. RBF神经网络在机器人视觉伺服控制中的应用[J].机床与液压,2015,43(15):41-43.
. Application of RBF Neural Networks in Visual Servo Control of Robots[J]. Machine Tool & Hydraulics,2015,43(15):41-43

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  • 在线发布日期: 2015-11-24
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