A Programming by Demonstration with Least Square Support Vector Machine for Manipulators

This paper presents a method of programming by demonstration, aiming at instructing the manipulator to accomplish tasks with obstacles in the way or with strict motion paths. Least square support vector machine LS-SVM, based on the principle of structure risk minimization, is employed to achieve better generalization and reproduced trajectories with higher accuracy. Furthermore, the velocity field method is applied to maintain the convergence of reproduced trajectories and smooth the motion. Finally, a series of obstacle avoidance experiments with a 7-DOF manipulator are conducted to verify the feasibility of the proposed method.

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