Unmanned surface vehicles

This experiment used different methodologies and comparisons that helped to determine the direction of future research on water-based perception systems for unmanned surface vehicles (USV) platforms. This would be using a stereo-vison based system. Presented in this work is object color and shape classification in the real-time maritime environment. This was coupled with HSV color space that allowed for different thresholds to be identified and detected. The algorithm was then calibrated and executed to configure the depth, color and shape accuracies. The approach entails the characterization of a stereo-vision camera and mount that was designed with 8.5° horizontal viewing increments and mounted on the WAMV.
This characterization has depth, color and shape object detection and its classification. Different shapes and buoys were used to complete the testing with assorted colors and shapes. The main program used was OpenCV which entails Gaussian blurring, Morphological operators and Canny edge detection libraries with a ROS integration. The code focuses on the area size and the number of contours detected on the shape for successes. A summary of what this thesis entails is the installation and characterization of the stereovision system on the WAMV-USV by obtaining specific inputs to the high-level controller.

This thesis presents the development a sliding mode controller and vehicle allocation to control a surface vessel platform within a high degree of accuracy. This is part of ongoing development on the WAMV platform at Florida Atlantic University to improve autonomy in marine systems. By developing models for the untested thrusters currently used, the efficacy of a Sliding Mode Controller is evaluated, and a new control allocation developed based on the gradient descent optimization method is developed to manage the thrusters’ constrained angles of thrust generation. The official simulation for the WAMV platform was then modified to include these aspects and the system was tested under wind conditions and was successful in achieving control to waypoints. The gradient descent optimization used for the control allocation did manage to increase the accuracy of both heading and position of the system at convergence. The sliding mode controller navigated to the desired waypoint however maintained oscillations of cross track that were less then 2m and heading error less 20 degrees.

Modeling, system identification and controller design for a 16’ catamaran is
described with the objective of enhanced operation in the presence of environmental
disturbances including wind, waves and current. The vehicle is fully-actuated in surge,
sway and yaw degrees of freedom. Analytical and experimental system identification is
carried out to create a numerical model of the vehicle. A composite system of a Multiinput
multi-output Proportional-Derivative (PD) controller and a nonlinear disturbance
observer is used for station-keeping and transiting modes of operation. A waypoint
transiting algorithm is developed to output heading and cross-track error from vehicle
position and waypoints. A control allocation method is designed to lower azimuthing
frequency and incorporate angle saturation and rate limits. Validation is achieved with
improvement in simulation with the addition of the nonlinear observer.