Visual tracking is one of the key components for robots
to accomplish a given task in a dynamic environment,
especially when independently moving objects are included.
This paper proposes an extension of Adaptive
Visual Servoing (hereafter, AVS) for unknown moving
object tracking. The method utilizes binocular stereo
vision, but does not need the knowledge of camera parameters.
Only one assumption is that the system
need stationary references in the both images by which
the system can predict the motion of unknown moving
objects. The basic ideas how we extended the AVS
method such that it can track unknown moving objects
are given and formalized into a new AVS system. The
experimental results with proposed control architecture
are shown and a discussion is given.
In this paper we describe a control methodology for
catching a fast moving object with a robot manipulator,
where visual information is employed to track the
trajectory of the target. Sensing, planning and control
are performed in real-time to cope with possible
unpredictable trajectory changes of the moving target,
and prediction techniques are adopted to compensate the
time delays introduced by visual processing and by the
robot controller. A simple but reliable model of the
robot controller has been taken into account in the
control architecture for improving the performance of the
system. Experimental results have shown that the robot
system is capable of tracking and catching an object
moving on a plane at velocities of up to 700 mm/s and
accelerations of up to 1500 mm/s2.