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Trajectory planning and tracking control for LED placement spray wax robot

机译:LED放置式喷蜡机器人的轨迹规划和跟踪控制

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For the motion system of a LED placement spray wax robot, this paper uses shortest path planning method of optimization theory to plan the robot's motion trajectory. It uses high order polynomial to plan spray wax robot's joint movement. Guided by the determining learning theory, this paper uses radial basis function (RBF) to design an adaptive neural network controller (ANNC). It tracks and controls the motion process of robot to move along the planned trajectory. This ensures the stability and rapidity of robot movement to achieve the purpose of save time and energy. Experiment is conducted using the algorithm designed in this paper, and comparison experiment with PID algorithm is also well done. The experimental results illustrate the effectiveness of the method designed in this paper.
机译:对于LED放置式喷蜡机器人的运动系统,本文采用最优化理论的最短路径规划方法来规划机器人的运动轨迹。它使用高阶多项式来计划喷蜡机器人的关节运动。在确定性学习理论的指导下,本文采用径向基函数(RBF)设计了自适应神经网络控制器(ANNC)。它跟踪并控制机器人沿计划轨迹移动的运动过程。这确保了机器人运动的稳定性和快速性,从而达到节省时间和精力的目的。利用本文设计的算法进行了实验,并与PID算法进行了比较实验。实验结果证明了本文设计方法的有效性。

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