Closed-loop uncertainty modeling for visual servoing

Robustness is the key feature for practical visual servoing systems. Uncertainty modeling in these systems is the first step towards accurate and robust visual servoing. Camera displacement error due to image noise has been investigated using the noise boundaries in the previous works. Also error covariance propagation has already been developed to model the uncertainties of different visual servoing system components. However, these works were either open-loop or not fully successful under controlled simulations. This work presents a new error modeling method based on error covariance propagation in closed-loop visual servoing systems, considering the discrete-time nature of the system. The proposed framework could be employed for a broad range of controllers. Simulation results suggest the effectiveness of the proposed method.