A First Step towards Hybrid Visual Servoing Control Based on Image Moments

The paper is concerned with a specific class of visual servoing problem, in which camera motion (including both translation and rotation) are constraint to be in the Z-axis direction. Such a constraint condition makes it possible to find appropriate image moments reflecting object depth and orientation. Image moments, as a kind of global image features, can be benefit to the performance of visual servoing system, such as insensitivity to image noise, nonsingularity in image Jacobian, and etc. In the paper, the mathematic relationships between image moments and object-depth-and-orientation are firstly introduced. Then appropriate image moments are selected, on the basis of which a hybrid visual servoing system is build. In our system, visual servoing controller consists of two parts: one is called translation controller which is in charge of object depth control, the other is called rotation controller which controls object orientation. The simulation results show that our hybrid visual servoing system performances well with a high accuracy.