We propose a new dynamically feasible trajectory generation algorithm that incorporates sternward motion for unmanned surface vehicles. This work is motivated by riverine applications where the operating environment is large and poorly known. We extend a navigation approach for forward path planning into a more versatile framework that includes safe and dynamically feasible backward trajectories. We pose the backward trajectory generation problem as a finite-horizon optimal control problem and transform it into a nonlinear programming problem by utilizing the direct shooting method. The nonlinear programming problem is solved using the Hooke-Jeeves numerical algorithm. We provide successful simulation and field-trial results that demonstrate the performance of backward path planning algorithm. / Master of Science

Trends in USV research will continue on the path toward a fully autonomous USV capable of troop transport or enemy engagement. Imaging sonar will be an integral part of this development. However, due in part to sonar's inherent physical limitations, as well as its sensitivity to environmental factors, sonar technology represents a bottleneck to the development of situationally aware USVs capable of high-speed maneuvers. The work presented in this thesis is intended to provide a platform to bridge this gap, which is the design, analysis, and field testing of a mount for an imaging sonar intended as a retrofit for an existing vessel. The result of this work represents a step toward the ultimate goal of a fully autonomous USV, and will enable the advancement of research in the use of imaging sonar on surface vehicles. This thesis examines the problem of mounting a sonar on a surface vehicle from a fundamental perspective. It describes the development of a list of customer needs, presents a prototype design, and presents the important analyses for the prototype. The prototype mount was built, and field testing for proof of concept was carried out on the Virginia Tech USV, which is a Rigid Hull Inflatable Boat (RHIB), and the Navy Special Operations Craft - Riverine (SOC-R) on the Pearl River at Stennis Space Center. Testing showed the mount to be highly effective at limiting risk to personnel and equipment while operating in difficult environments like swamps. However, it also exposed some limitations associated with the mount's breakaway device, and the mounting location at the side in 2012, and at the stern in 2013. Based on experience gained from testing, a new mount design is presented for use at the bow. The bow location offers better impact protection to the sonar as long as the sonar can be positioned above the boat's draft. Field tests also exposed the need for an omnidirectional breakaway device which limits impact loads on the sonar during collisions. The Ball and Socket Breakaway (BSB) device was designed to satisfy this need. The BSB is acts as a "mechanical fuse," which holds the sonar rigidly under normal operating conditions, but will slip and rotate when the sonar strikes an object. It is designed to respond to impact loads on the sonar from the front, sides, or back, resulting in improved sonar protection during the varied maneuvers necessary for operation in shallow, narrow passageways. The expected moment holding capacity of the BSB as it is currently designed is 300 N-m (2650 lb-in), which should allow for speeds up to 3 m/s (6 kt) before drag-induced breakaway. / Master of Science

This thesis is about a robust filtering method known as the interval Kalman filter (IKF), an extension of the Kalman filter (KF) to the domain of interval mathematics. The key limitation of the KF is that it requires precise knowledge of the system dynamics and associated stochastic processes. In many cases however, system models are at best, only approximately known. To overcome this limitation, the idea is to describe the uncertain model coefficients in terms of bounded intervals, and operate the filter within the framework of interval arithmetic. In trying to do so, practical difficulties arise, such as the large overestimation of the resulting set estimates owing to the over conservatism of interval arithmetic. This thesis proposes and demonstrates a novel and effective way to limit such overestimation for the IKF, making it feasible and practical to implement. The theory developed is of general application, but is applied in this work to the heading estimation of the Springer unmanned surface vehicle, which up to now relied solely on the estimates from a traditional KF. However, the IKF itself simply provides the range of possible vehicle headings. In practice, the autonomous steering system requires a single, point-valued estimate of the heading. In order to address this requirement, an innovative approach based on the use of machine learning methods to select an adequate point-valued estimate has been developed. In doing so, the so called weighted IKF (wIKF) estimate provides a single heading estimate that is robust to bounded model uncertainty. In addition, in order to exploit low-cost sensor redundancy, a multi-sensor data fusion algorithm compatible with the wIKF estimates and which additionally provides sensor fault tolerance has been developed. All these techniques have been implemented on the Springer platform and verified experimentally in a series of full-scale trials, presented in the last chapter of the thesis. The outcomes demonstrate that the methods are both feasible and practicable, and that they are far more effective in providing accurate estimates of the vehicle’s heading than the conventional KF when there is uncertainty in the system model and/or sensor failure occurs.

This dissertation addresses the modeling, identification, and control of an automated planing vessel. To provide motion models for trajectory generation and to enable model-based control design for trajectory tracking, several experimentally identified models are compared over a wide range of speed and planing conditions for the Virginia Tech Ribcraft Unmanned Surface Vehicle. The modeling and identification objective is to determine a model which is sufficiently rich to enable effective model-based control design and trajectory optimization, sufficiently simple to allow parameter identification, and sufficiently general to describe a variety of hull forms and actuator configurations. Beginning with a 6 degree of freedom nonlinear dynamic model, several linear steering and speed models are obtained as well as a thruster model. The Ribcraft USV tracks trajectories generated with the selected maneuvering models by using a back- stepping trajectory controller. A PD cascade trajectory control law is also developed and the performance of the two controllers is compared using aggressive trajectories. The backstepping control law compares favorably to the PD cascade controller. The backstepping control law is then further modified to account for nonlinear sternward dynamics and for a constant or slowly varying fluid flow. / Ph. D.

The majority of the Earths surface is covered with water, and the air-water interface (AWI) acts as the natural boundary between the atmosphere and the water. The AWI is an important ecological zone in natural aquatic habitats that governs transport of material and energy between bodies of water and the atmosphere. Little is known about temperature profiles and biological transport across the boundary layers at the air-water interface, and how wind interactions at the AWI affects them. New technologies such as sensors and unmanned surface vehicles (USV) need to be developed and used to address this knowledge gap. The goal of the research is to study population densities of the bacteria Pseudomonas syringae below, at and above the AWI using USV equipped with specialized sensors. The first specific objective was to map temperature profiles and resolve the boundary layer at the AWI using high resolution distributed temperature sensing (HR-DTS) on board an unmanned surface vehicle (USV). Our second research objective was to sample microbes from the water with a USV at multiple depths and locations. Our third research objective was to sample microbes from the atmosphere with a USV at the AWI. Our fourth research objective was to track and localize hazardous agents (tracer dyes) using a USV in aqueous environments. / Ph. D. / The majority of the Earths surface is covered with water, and the air-water interface (AWI) acts as the natural boundary between the atmosphere and the water. The AWI is an important ecological zone in natural aquatic habitats. Little is known about temperature profiles and biological transport across the boundary layers at the air-water interface, and new technologies need to be developed and used to address this knowledge gap. The specific objectives of the proposed work are to: (1) map temperature profiles and resolve the boundary layer at the AWI using high resolution distributed temperature sensing (HR-DTS) on board an unmanned surface vehicle (USV), (2) sample microbes from the water with a USV at multiple depths and locations, (3) sample microbes from the atmosphere with a USV at the AWI, and (4) track and localize hazardous agents (tracer dyes) using a USV in aqueous environments.

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.

The usage of autonomous vehicles is starting to appear in several different domains and the domain of public safety is no exception. Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) has created a research arena for public safety (WARA-PS) to explore experimental features, usages, and implementation of autonomous vehicles within the domain of public safety. Collaborating in the arena are several companies, universities, and researchers. This thesis examines, in collaboration with Combitech, a company partnered in WARA-PS, how the implementation of autonomous vehicles affects the sociotechnical system of a search and rescue operation during a drifting boat with potential castaways. This is done by creating a case together with domain experts, analyzing the sociotechnical system within the case using cognitive work analysis and then complementing the analyses with the unmanned autonomous vehicles of WARA-PS. This thesis has shown how the WARA-PS vehicles can be implemented in the case of a drifting boat with potential castaways and how the implementation affects the sociotechnical system. Based on the analyses and opinions of domain experts’ future guidelines has been derived to further the work with sociotechnical aspects in WARA-PS. / WARA-PS