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A Trajectory Tracking Application of Redundant Planar Robot Arm via Support Vector Machines

机译:支持向量机在平面冗余机器人手臂轨迹跟踪中的应用

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摘要

In this paper we present a kinematic based trajectory tracking application of redundant planar robot arm by using support vector machine method (SVM). The main advantages of using the proposed method are that, it does not suffer from singularity that is the main problem of redundancy in robot kinematics and better results for the kinematic model of redundant robot arm can be obtained by using less training data. Training data are obtained by using the forward differential kinematic model of the robot arm. We also implement the trajectory tracking application by using Artificial Neural Networks (ANN). Two methods are compared with respect to their generalization performances, and training performance. Simulation results are given.
机译:在本文中,我们提出了一种基于运动学的冗余平面机器人手臂运动轨迹跟踪应用支持向量机方法(SVM)。使用所提出的方法的主要优点是,它不会受到奇异性的影响,而奇异性是机器人运动学中冗余的主要问题,并且通过使用较少的训练数据可以得到冗余的机器人手臂运动学模型的更好结果。训练数据是通过使用机器人手臂的正向运动学模型获得的。我们还通过使用人工神经网络(ANN)实现了轨迹跟踪应用程序。比较了两种方法的泛化性能和训练性能。给出了仿真结果。

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