This paper is dedicated to vision-based modeling and control of large-dimension parallel robots driven by inextensible cables of non-negligible mass. An instantaneous inverse kinematic model devoted to vision is introduced. This model relies on the specificities of a parabolic profile hefty cable modeling and on the resulting simplified static analysis. By means of a kinematic visual servoing method, computer vision is used in the feedback loop for easier control. According to the modeling derived in this paper, measurements that allow the implementation of this visual servoing method consist of the mobile platform pose, the directions of the tangents to the cable curves at their drawing points and the cable tensions. The proposed visual servoing scheme will be applied to the control of a large parallel robot driven by eight cables. To this end, in order to obtain the aforementioned desired measurements, we plan to use a multi-camera setup together with force sensors.

No abstract

One of the main drawbacks of vision-based control that remains unsolved is the poor dynamic performances caused by the low acquisition frequency of the vision systems and the time latency due to processing. We propose in this paper to face the challenge of designing a high-performance dynamic visual servo control scheme. Two versatile control laws are developed in this paper: a position-based dynamic visual servoing and an image-based dynamic visual servoing. Both control laws are designed to compute the control torques exclusively from a sequential acquisition of regions of interest containing the visual features to achieve an accurate trajectory tracking. The presented experiments on vision-based dynamic control of a high-speed parallel robot show that the proposed control schemes can perform better than joint-based computed torque control.