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

Abstract

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.