Ph. D. Thesis.Control and navigation systems are key for any autonomous robot. Due to environmental
disturbances, model uncertainties and nonlinear dynamic systems, reliable functional control is
essential and improvements in the controller design can significantly benefit the overall
performance of Unmanned Underwater Vehicles (UUVs). Analogously, due to electromagnetic
attenuation in underwater environments, the navigation of UUVs is always a challenging
problem.
In this thesis, control and navigation systems for UUVs are investigated. In the control field,
four different control strategies have been considered: Proportional-Integral-Derivative Control
(PID), Improved Sliding Mode Control (SMC), Backstepping Control (BC) and customised
Fuzzy Logic Control (FLC). The performances of these four controllers were initially simulated
and subsequently evaluated by practical experiments in different conditions using an underwater
vehicle in a tank. The results show that the improved SMC is more robust than the others with
small settling time, overshoot, and error.
In the navigation field, three underwater visual navigation systems have been developed in the
thesis: ArUco Underwater Navigation systems, a novel Integrated Visual Odometry with
Monocular camera (IVO-M), and a novel Integrated Visual Odometry with Stereo camera
(IVO-S). Compared with conventional underwater navigation, these methods are relatively
low-cost solutions and unlike other visual or inertial-visual navigation methods, they are able to
work well in an underwater sparse-feature environment. The results show the following: the
ArUco underwater navigation system does not suffer from cumulative error, but some segments
in the estimated trajectory are not consistent; IVO-M suffers from cumulative error (error ratio is
about 3 - 4%) and is limited by the assumption that the “seabed is locally flat”; IVO-S suffers
from small cumulative errors (error ratio is less than 2%).
Overall, this thesis contributes to the control and navigation systems of UUVs, presenting the
comparison between controllers, the improved SMC, and low-cost underwater visual navigation
methods