The problem studied in this thesis is control of robots using information
from optronic sensors. With a laser range sensor onboard the robot the
relative distance to an object can be measured. This allows the robot to
operate in a partial unknown environment. One complication with non-contact
sensors is the assiciation problem, i.e. finding the correspondence between
the measured signals and each object in an unstructured workspace. This
problem is addressed in the algorithms presented for using measurements. The
approach is model based with respect to sensor errors, uncertainty in
association and robot dynamics. Results includes:
* The range weighted Hough transform (RWHT) was developed as a robust
algorithm for extracting plane surfaces in scans made by a range measuring
laser. The peaks in the RWHT are used during navigation of mobile robots and
for automatic generation of maps.
* A modelling study is made toward improving mobile robot performance using
rate gyros. The main limitation seems to be an unknown lateral velocity. The
special kinematic for navigating articulated vehicles is also studied.
* An hydraulic arm, without joint angle encoders, is controlled with feedback
from measured directions to retro-reflectors. An eye-in-hand range camera is
studied with respect to gripping and for reducing vibration.
Considering the fast development in computing and laser based sensing there
is a large potential for novel application like robots in contaminated areas,
in mining, in forests etc. The model-based approach in well suited for
industrial requirements on predictable properties and self-monitoring of
control and information systems.