Target Tracking for Visual Servoing Systems Based on an Adaptive Kalman Filter

Author:

Liu Chang1,Huang Xinhan1,Wang Min1

Affiliation:

1. Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, P. R. China

Abstract

Visual servoing has been around for decades, but time delay is still one of the most troublesome problems to achieve target tracking. To circumvent the problem, in this paper, the Kalman filter is employed to estimate the future position of the object. In order to introduce the Kalman filter, accurate time delays, which include the processing lag and the motion lag, need to be obtained. Thus, the delays of the visual control servoing systems are discussed and a generic timing model for the system is provided. Then, we present a current statistical model for a moving target. A fuzzy adaptive Kalman filter, which is evolved from the Kalman filter, is introduced based on the current statistical model. Finally, a two DOF visual controller based variable structure control law for micro-manipulation is presented. The results show that the proposed adaptive Kalman filter can improve the ability to track moving targets.

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

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