Abstract
Nowadays, in fields of robot vision, a control method called visual servoing attracts attention. The visual servoing is a method to control robots by visual information in a feedback loop, which is obtained by visual sensors. So, this method is expected to be able to have robots adapt to tasks in changing or unknown environment. However, when the target object moves quickly, it happens to be unable for the machine to track it due to robots' motion delay. To decrease the delay time, we have proposed prediction servoing control method, which is the method of predicting the position of the target object based on the past position data of the object and learning of neural networks, and utilize it as a desired position for the visual servoing. In this research we have confirmed how the learnig function in neural networks work for precise prediction of target's future position through visual servoing experiments.
