This thesis deals with Visual Servoing and its strictly connected disciplines like projective
geometry, image processing, robotics and non-linear control. More specifically the
work addresses the problem to control a robotic manipulator through one of the largely
used Visual Servoing techniques: the Image Based Visual Servoing (IBVS). In Image
Based Visual Servoing the robot is driven by on-line performing a feedback control loop
that is closed directly in the 2D space of the camera sensor. The work considers the case
of a monocular system with the only camera mounted on the robot end effector (eye
in hand configuration). Through IBVS the system can be positioned with respect to a
3D fixed target by minimizing the differences between its initial view and its goal view,
corresponding respectively to the initial and the goal system configurations: the robot
Cartesian Motion is thus generated only by means of visual informations.
However, the execution of a positioning control task by IBVS is not straightforward because
singularity problems may occur and local minima may be reached where the reached
image is very close to the target one but the 3D positioning task is far from being fulfilled:
this happens in particular for large camera displacements, when the the initial and the
goal target views are noticeably different.
To overcame singularity and local minima drawbacks, maintaining the good properties of
IBVS robustness with respect to modeling and camera calibration errors, an opportune
image path planning can be exploited. This work deals with the problem of generating
opportune image plane trajectories for tracked points of the servoing control scheme (a
trajectory is made of a path plus a time law). The generated image plane paths must be
feasible i.e. they must be compliant with rigid body motion of the camera with respect
to the object so as to avoid image jacobian singularities and local minima problems. In
addition, the image planned trajectories must generate camera velocity screws which are
smooth and within the allowed bounds of the robot. We will show that a scaled 3D motion
planning algorithm can be devised in order to generate feasible image plane trajectories.
Since the paths in the image are off-line generated it is also possible to tune the planning
parameters so as to maintain the target inside the camera field of view even if, in some
unfortunate cases, the feature target points would leave the camera images due to 3D
robot motions.
To test the validity of the proposed approach some both experiments and simulations
results have been reported taking also into account the influence of noise in the path
planning strategy. The experiments have been realized with a 6DOF anthropomorphic
manipulator with a fire-wire camera installed on its end effector: the results demonstrate
the good performances and the feasibility of the proposed approach