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.
This paper studies the problem of TRACKING a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
This paper studies the problem of TRACKING a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
