Dynamic visual servoing with Kalman filter-based depth and velocity estimator

A new adaptive Kalman filter applied to visual servoing tasks

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

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 ...

Improvement of the Prediction Quality for Visual Servoing with a Switching Kalman Filter

The main control problem of visual servoing is to cope with the delay introduced by image acquisition and image processing. This delay is the main reason for limited tracking velocity and acceleration. Predictive algorithms are one solution to handle the delay. The drawback of prediction algorithms is the bad prediction behavior for the discontinuity in the target motion, for example, a velocit...

Visual servoing based on dynamic vision

This paper deals with the way to achieve positioning tasks by visual servoing in the case of planar and motionless objects whose shape is unknown. In fact, we consider here complex objects like those one can encount in the agrifood industry. A 3D reconstruction phase is first considered yielding to the parameters of the plane. This computation is based on the measurement of the 2D velocity in a...

Depth Observation for Image - based Visual Servoing : Theory

In the classical image-based visual servoing framework, error signals are directly computed from image feature parameters, allowing, in principle, control schemes to be obtained that need neither a complete three-dimensional (3D) model of the scene nor a perfect camera calibration. However, when the computation of control signals involves the interaction matrix, the current value of some 3D par...