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No description available.

In a variety of military operations, a convoy of autonomous followers may need to traverse the leader's path without using Global Positioning System (GPS), lane markers/magnets and/or a vision-based vehicle-following system. This can be achieved by using Visual Teach and Repeat (VT and R), which provides an effective method for autonomous repeating of a previously driven path. This thesis describes the design of a distributed control system that uses the idea behind the VT and R method to allow a convoy of inter-communicable autonomous vehicles to follow a manually-driven lead vehicle's path with a desired inter-vehicle spacing, even when the leader is not in the camera view of the followers. The longitudinal controller is designed for addressing a 1D spacing problem and then combined with a path tracker for tracking a path in a 2D environment. The designed control model is tested in simulations.

In a variety of military operations, a convoy of autonomous followers may need to traverse the leader's path without using Global Positioning System (GPS), lane markers/magnets and/or a vision-based vehicle-following system. This can be achieved by using Visual Teach and Repeat (VT and R), which provides an effective method for autonomous repeating of a previously driven path. This thesis describes the design of a distributed control system that uses the idea behind the VT and R method to allow a convoy of inter-communicable autonomous vehicles to follow a manually-driven lead vehicle's path with a desired inter-vehicle spacing, even when the leader is not in the camera view of the followers. The longitudinal controller is designed for addressing a 1D spacing problem and then combined with a path tracker for tracking a path in a 2D environment. The designed control model is tested in simulations.

An autonomous system has been widely applied for various civil/military research because of its versatile capability of understanding high-level intent and direction of a surrounding environment and targets of interest. However, as autonomous systems can be out of control to cause serious loss, injury, or death in the worst case, the verification of their functionalities has got increasing attention. For that reason, this study is focused on the verification of a heterogeneous multi-agent autonomous system. The thesis first presents an overview of formal methods, especially focuses on model checking for autonomous systems verification. Then, six case studies are presented to verify the decision making behaviours of multi-agent system using two basic scenarios: surveillance and convoy. The initial system considered in the surveillance mission consists of a ground control system and a micro aerial vehicle. Their decision-making behaviours are represented by means of Kripke model and computational tree logic is used to specify the properties of this system. For automatic verification, MCMAS (Model Checker for Multi-Agent Systems) is adopted due to its novel capability to accommodate the multi-agent system. After that, the initial system is extended to include a substitute micro aerial vehicle. These initial case studies are then further extended based on SEAS DTC exemplar 2 dealing with behaviours of convoy protection. This case study includes now a ground control system, an unmanned aerial vehicle, and an unmanned ground vehicle. The MCMAS successfully verifies the targeting behaviours of the team-level unmanned systems. Reversely, these verification results help retrospectively improve the design of decision-making algorithms by considering additional agents and behaviours during four steps of scenario modification. Consequently, the last scenario deals with the system composed of a ground control system, two unmanned aerial vehicles, and four unmanned ground vehicles with fault-tolerant and communications relay capabilities. In conclusion, this study demonstrates the feasibility of model checking algorithms as a verification tool of a multi-agent system in an initial design stage. Moreover, this research can be an important first step of the certification of multi-agent autonomous systems for the domains of robotics, aerospace and aeronautics.

Distributed generation along with smart grid applications are poised to make important contributions to the clean-tech sector and remote communities. The dependence on one source for energy supply does not prove reliable enough when the renewable resource, such as wind or solar, is variable, creating a dependence on external fuel supply and a vulnerability to foreign control. Developing an energy strategy through intelligent energy system simulation and optimization can help communities make informed decisions about their energy investments. This dissertation reasons that distributed renewable energy systems without operative computational infrastructures face a fundamental economic challenge derived from their ad-hoc design and implementation. To address this, it proposes the method of Optimal Operational Awareness (OOA)—a feedback mechanism on the state of, and changes in, the properties of the implemented subsystems and their behaviour, to meet users objectives. Despite many applications of hybrid renewable energy systems, and reputable multi-objective evolutionary algorithms (MOEAs) for optimization, no one has applied MOEAs to dynamic system operation for optimized engagement of system components. This thesis describes an application of the NSGA-II algorithm to the multi-objective optimization of the operation of a stand-alone wind-PV-biomass-diesel system with batteries and CAES storage and a central controller. The simultaneous objectives are to minimize the levelized cost of energy (LCOE), and unmet load (UL) while maximizing the renewable energy ratio (RER). This work provides a case-study evaluation from data collected on-site at the island of Fernando de Noronha (FDN), Brazil. The results show that FDN could move from an annual average of 33% RER and LCOE range of $0.26 - $0.36 per kWh to an increased RER range of 60% - 100% and LCOE of $0.10 - $0.50 per kWh, while maintaining UL of 0%, by increasing its renewable energy generation and storage capacity approximately five times. Furthermore, optimal operational awareness for this configuration shows that despite 100% RER, certain periods experience a high LCOE of $2.00 per kWh, resulting from energy spillage due to oversupply, indicating sub-optimal system sizing and wasted energy to trim by improving system configuration. This work concludes that it is possible to achieve 100% RER, but storage and/or backup diesel generation are important to include in systems with highly variable supply. The cost of electricity decreases as renewable energy penetration increases, but is configuration dependent as well dependent on storage state of charge. Oversizing storage can be just as costly, if not more costly, than supplying energy with diesel generation, thus proper sizing and dispatch strategy are critical to achieve economic electricity supply. Furthermore, the role of multiple renewable energy generators in providing autonomous supply can be more valuable to the user than increased supply cost.

In this thesis seafloor cold vents are examined using autonomous underwater vehicle (AUV) and remotely operated vehicle (ROV) data on the Northern Cascadia margin. These data were collected in a 2009 joint cruise between the Monterey Bay Aquarium Research Institute (MBARI) and Natural Resources Canada (NRCan). High- resolution bathymetry data, acoustic reflectivity (backscatter) data, and 3.5 kHz sub bottom profiler data were examined for cold-vent-related features that include pockmarks, chemosynthetic biological communities (CBC), and authigenic carbonate. Additionally subsequent ROV observations, sediments from push cores and seafloor video/photos were used to ground truth AUV data. Numerous prolific venting sites were examined in detail and a model for the evolution of venting was generated. Vents are categorized as juvenile, intermediate, or mature depending on the presence and or absence of cold-vent-features. High near-surface reflection amplitudes are coincident with an anomalous area of seafloor backscatter. In June of 2012, NEPTUNE (North East Pacific Time-series Underwater Networked Experiment) collected a near-surface push core with their ROV ROPOS (Remotely Operated Platform for Ocean Sciences) in the high reflective area. The retrieved core showed stacked turbidites in the top 0.5 meters of the sediment column. Closely spaced high-velocity turbidite sands are highly reflective and inhibit acoustic penetration to depth. The presence of high-density, high-velocity sands in the near surface is linked to steady ocean bottom currents. These bottom currents progress northeast to southwest over the study area and differentially erode the surface sediments by removing muds and leaving heavy sands over the exposed area. / Graduate / 0373 / 0374 / jonfurlong@hotmail.com

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Increased interestin In-Situ Resource Utilization (ISRU) concept for lunar outpost construction has motivated to the development of autonomous excavation rovers. The system design of two autonomous excavation rover prototypes UNEMEEP and The Musketeers are detailed in this thesis. The problem of autonomous excavation has been explored in the area of agriculture and mining. However, to date very little have been accomplished in the area of an autonomous excavation rover aimed towards space application. A hybrid position and admittance control strategy is implemented on autonomous excavation rovers to achieve digging and leveling capabilities. Integration tests and a full scale multirover mission scenario were also carried out. The results from the experiments are analyzed and recommendations are made to improve upon the capabilities of the rovers.

Increased interestin In-Situ Resource Utilization (ISRU) concept for lunar outpost construction has motivated to the development of autonomous excavation rovers. The system design of two autonomous excavation rover prototypes UNEMEEP and The Musketeers are detailed in this thesis. The problem of autonomous excavation has been explored in the area of agriculture and mining. However, to date very little have been accomplished in the area of an autonomous excavation rover aimed towards space application. A hybrid position and admittance control strategy is implemented on autonomous excavation rovers to achieve digging and leveling capabilities. Integration tests and a full scale multirover mission scenario were also carried out. The results from the experiments are analyzed and recommendations are made to improve upon the capabilities of the rovers.