Uncalibrated Neuro-Visual Servoing Control for Multiple Robot Arms

Abstract

Diverse image-based tracking schemes for a robot moving in free motion have been proposed and experimentally validated. However, few visual servoing schemes have addressed the tracking of the desired trajectory and the contact forces for multiple robot arms. The main difficulty stems from the fact that camera information cannot be used to drive force trajectories. Recognizing this fact, a unique error manifold that includes position-velocity and force errors in orthogonal complements is proposed. A synergistic scheme that fuses camera, encoder and force sensor signals into a unique error manifold allows proposing a control system which guarantees exponential tracking errors under parametric uncertainty. Additionally a small neural network driven by a second order sliding mode surface is derived to compensate robot dynamics. Residual errors that arise because of the finite size of the neural network are compensated via an orthogonalized second order sliding mode. The performance of the proposed scheme, in two significant applications of the multiple robot arms, is validated through numerical simulations.