An, Edgar

Autonomous Underwater Vehicle (AUV) depth control methods typically use a
pressure sensor to measure the depth, which results in the AUV following the trajectory
of the surface waves. Through simulations, a controller is designed for the Ocean
Explorer AUV with the objective of the AUV holding a constant depth below the still
water line while operating in waves. This objective is accomplished by modeling sensors
and using filtering techniques to provide the AUV with the depth below the still water
line. A wave prediction model is simulated to provide the controller with knowledge of
the wave disturbance before it is encountered. The controller allows for depth keeping
below the still water line with a standard deviation of 0.04 and 0.65 meters for wave
amplitudes of 0.1-0.25 and 0.5-2 meters respectively and wave frequencies of 0.35-1.0
𝑟𝑎𝑑⁄𝑠𝑒𝑐, and the wave prediction improves the depth control on the order of 0.03 meters.

This thesis describes the development of the hardware-in-the-loop simulation for FAU Autonomous Underwater Vehicles. The development was based on the existing simulation platform. For more efficiency and flexibility, this simulation package was ported to Linux. The hardware-in-the-loop simulation enables developers to connect the vehicle directly to a remote simulator. This kind of simulation is used to test the actual software components embedded in the vehicle system. The simulation package was enhanced by the addition of a 3D viewer. This thesis describes the whole development process, from feasibility study and implementation to qualification phases. This viewer is platform independent and designed to be connected to the simulator. It renders the AUV moving in a virtual environment. This tool can be used during all development steps, from tuning phases to post-mission analysis.

The rapid increase in the amount of data gathered by Autonomous Underwater Vehicles (AUV) leads to a global data management issue. Indeed, this large data collection effort is only interesting if the data collected can be easily retrieved and analyzed by many researchers. The main contribution of this thesis is the design of data management and retrieval schemes useful to the whole AUV community that both simplify the access and treatment of the data collected. This is achieved by the use of a self-describing standard data format (Hierarchical Data Format) and the use of Internet browsers' file download ability. Recent developments in Sun's Java applet technology have been used to provide a user-friendly Graphical User Interface (GUI) so that the user can select data files according to a large number of parameters (what variables have been collected, when and where).

This thesis describes the development of a simulation environment for Autonomous Underwater Vehicles (AUVs) on UNIX platforms. AUV missions can therefore be carried out without going to the sea. The Yoyo controller, a component for AUVs is also described in this thesis. The main function of Yoyo is to control the vertical profile of an AUV while it is navigating underwater performing data collection missions. The development of the controller is done in the simulation environment. Several test cases have been performed, and the test results have clearly demonstrated the successful development of the controller.

Response time to a threat or incident for coastline security is an area needing improvement. Currently, the U.S. Coast Guard is tasked with monitoring and responding to threats in coastal and port environments using boats or planes, and SCUBA divers. This can significantly hinder the response time to an incident. A solution to this problem is to use autonomous underwater vehicles (AUVs) to continuously monitor a port. The AUV must be able to navigate the environment without colliding into objects for it to operate effectively. Therefore, an obstacle avoidance system (OAS) is essential to the activity of the AUV. This thesis describes a systematic approach to characterize the OAS performance in terms of environments, obstacles, SONAR configuration and signal processing methods via modeling and simulation. A fuzzy logic based OAS is created using the simulation. Subsequent testing of the OAS demonstrates its effectiveness in unknown environments.

This thesis presents a method for modeling navigation sensors used on ocean systems and particularly on Autonomous Underwater Vehicles (AUV). An extended Kalman filter was previously designed for the implementation of the Inertial Navigation System (INS) making use of Inertial Measurement Unit (IMU), a magnetic compass, a GPS/DGPS system and a Doppler Velocity Log (DVL). Emphasis is put on characterizing the static sensor error model. A "best-fit ARMA model" based on the Aikake Information Criterion (AIC), Whiteness test and graphical analyses were used for the model identification. Model orders and parameters were successfully estimated for compass heading, GPS position and IMU static measurements. Static DVL measurements could not be collected and require another approach. The variability of the models between different measurement data sets suggests online error model estimation.

This thesis describes the determination of linear and nonlinear coefficients for the Morpheus vehicle. Added mass and nonlinear damping terms were obtained by strip-theory. These added mass coefficients were compared to the ones previously computed by boundary-integral method. Open-loop simulations were conducted using both sets of added-mass coefficients along with the damping terms, which were adjusted to fit at-sea data. A previously estimation technique for hydrodynamic coefficients has been applied to the Morpheus AUV using a Kalman filter. This technique based on linearized equations of motion was tested with linear and nonlinear data generated by simulation. Steering and diving motions were considered resulting in the estimation of different sets of coefficients. Results showed that the estimated values were able to reproduce accurately the vehicle motion in the linear as well as in the nonlinear case.

This thesis presents the design and implementation of an underwater network communication protocol. The goal is to enable several autonomous underwater vehicles (AUVs) to form a communication network and to exchange information during at-sea missions. The focus of this work is on the upper layers of the protocol: Network and Transport layers. Routing is a critical issue since all the nodes forming the network are moving. A study and comparison of existing routing algorithms is presented. Two routing algorithms have been chosen and implemented in the network layer of the protocol: Flooding and Destination Sequence Distance Vector Routing. The protocol has been tested on several types of simulated missions. An analysis of the results is proposed for each mission.

This thesis describes an automated post-processing tool, designed for use on navigational data gathered by Autonomous Underwater Vehicles (AUVs), developed and operated by the Department of Ocean Engineering at Florida Atlantic University. The post-processing tool consists of a 9-state complementary Kalman filter in conjunction with a Rauch-Tung-Striebel (RTS) smoothing algorithm. The Kalman filter is run forward in time to merge navigational data from an Inertial Measurement Unit (IMU), a Doppler Velocity Log (DVL), a magnetic compass, a GPS/DGPS system and an Ultrashort Baseline (USBL) tracking system. Subsequently, the RTS smoothing algorithm is run backwards in time to find and compensate for drift errors in dead reckoned position and compass measurement error. The post-processing tool has been implemented as a graphical user interface, designed in MATLAB. Improved accuracy in post-processed position and heading has been verified by conducting sea trials and post-processing the collected data.

This thesis describes the implementation of a commercially available forward looking sonar (FLS) in an autonomous underwater vehicle (AUV) modified for the task of reactive obstacle detection. Any obstacle lying in the vehicle's path is a potential mission-terminating threat. Inclusion of a forward looking sensor would provide valuable information to the AUV. Threat assessment and navigation would use this information in order to avoid obstacles. The system used for this project is an 8-element transducer FLS at 200 kHz. The sonar control software is done in DOS on a dedicated personal computer in a PC/104 form factor. A variable cell-size grid occupancy search method is used to detect objects in the vehicle path. This thesis describes how this sonar is used for the obstacle detection task (software), how it is integrated (hardware and network) in the AUV and what are the results obtained with the system.