Performance-oriented networked visual servo control with sending rate scheduling

In order to speed up image processing in visual servoing, the distributed computational power across networks and appropriate data transmission mechanisms are of particular interest. In this paper, a high sampling rate of visual feedback is achieved by distributed computation on a cloud image processing platform. For target tracking with a networked visual servo control system, a switching control law considering the varying feedback delay caused by image processing and data transmission is applied to improve the control performance. A sending rate scheduling strategy aiming at saving the network load is proposed based on the tracking error. Experiments on a 7 degree-of-freedom (DoF) manipulator are carried out to validate the proposed approach. The proposed approach shows a similar control performance as a system without sending rate scheduling, however, beneficially with largely reduced network load.