LAUSR

Large-scale deployable cable-driven robots face a lack of kinematic precision, and the cable dynamics impose considerable challenges in terms of controller design. The problem’s complexity increases because a deployable robot may not exploit expensive and highly accurate of measurement devices. Thus, it is necessary to efficiently combine the set of measurements available through low-cost sensors to track the end-effector’s position and reduce the oscillations. This paper’s main contribution is to propose a novel feedback method for fusing the vision and joint kinematic sensors for achieving suitable tracking performance. To this end, the dynamic formulation of a large-scale deployable cable-driven robot has been derived considering a lumped mass model for the cables. Based on this model, it is then shown that the stability conditions are satisfied through a suitable combination of sensory data incorporated into the control law. Finally, the performance for the proposed controller has been illustrated using the experimental results on a deployable suspended cable-driven robot showing the effectiveness of the proposed methodology regardless of the underlying system uncertainties.