On-Line Estimation of Jacobian Matrix Based on Particle Filter

摘要

Proposes a new method of estimating Jacobian matrixes on-line for image-based robot visual servo systems.A vector is firstly formed from the elements of a Jacobian matrix,and the problem is converted into one of state-estimation.Particle filtering suitable for non-liner nonGaussian systems is utilized to solve the Jacobian estimation problem.The proposed method and the one based on Kalman filtering are tested to track a moving target on a two-degree-of-freedom system with non-Gaussian noise.The results showed the effectiveness and the robustness of the proposed method.System calibrations can be avoided and no specification on system noises is needed.