Abstract
In this article, configuration adjustment (CA) for robot manipulators at the joint-acceleration level is presented. Specifically, a new acceleration-level performance index for achieving CA is designed by employing the neurodynamic method. Thus, based on this performance index, and by incorporating joint physical constraints (i.e., joint-configuration, -velocity, and -acceleration limits), a novel acceleration-level CA (ALCA) scheme for robot manipulators is proposed and investigated. The proposed ALCA scheme is transformed into a quadratic program and calculated using a neural network solver. Comparative simulation results obtained with a four-link robot manipulator are presented to substantiate the effectiveness and superiority of the proposed ALCA scheme compared with those of the velocity-level CA scheme. Moreover, simulations and experiments are conducted on a practical Epson robot manipulator to demonstrate the physical realization of the proposed ALCA scheme.
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