Robotics Commons^™

A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane

Doctoral Dissertations and Master's Theses

This research presents a quantitative performance comparison between light detection and ranging (LiDAR) and vision-based sensing for real-time maritime object detection on autonomous surface vessels. Using Embry-Riddle Aeronautical University’s (ERAU) Minion platform and 2024 Maritime RobotX Challenge data, this study evaluates the detection of six maritime object categories using two representative models. YOLOv8 provides a neural network vision-based method, and GB-CACHE provides a deterministic LiDAR-based method. Both models have been previously demonstrated to run in real time on uncrewed surface vessels (USVs). The evaluation methodology encompasses multi-sensor calibration, real-time performance analysis, and the introduction of a late-fusion strategy in the …

Orbital Maneuvers And Interplanetary Trajectory Design Via Reinforcement Learning, Roberto Cuéllar Rangel

Doctoral Dissertations and Master's Theses

This dissertation investigates the application of reinforcement learning (RL) to the design and optimization of low-thrust spacecraft trajectories, with an emphasis on autonomy, adaptability, and robustness in the presence of system uncertainties and unmodeled perturbations. Classical approaches to low-thrust trajectory design are predominantly grounded in optimal control theory, which relies on the availability of precise dynamical models and often requires problem-specific reformulation and solver tuning. While optimal control methods offer high accuracy under deterministic conditions, their sensitivity to stochastic disturbances and computational limitations in highly nonlinear or uncertain environments pose significant challenges for future autonomous space missions.

To address these …

Studying The Performance Of Object Recognition With Fusion Of Visible Light And Infrared Images With Neural Networks, Plamen Petkov

Doctoral Dissertations and Master's Theses

Neural networks have been used for object detection and recognition in both color and intensity camera images. As the use of infrared cameras, colloquially termed thermal cameras, has increased and costs have decreased, object detection and recognition in infrared camera images have been increasingly studied. An infrared image is treated as an intensity image, just like a grayscale camera image, except the intensity corresponds to infrared radiation instead of visible light. The information provided by these two types of images are different, especially in different lighting and environmental situations, and some types of objects are more easily recognized in visible …

Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments, Ayush Raminedi

Doctoral Dissertations and Master's Theses

In the modern world, various missions are being carried out under the assistance of autonomous flight vehicles due to their ability to operate in a wide range of flight conditions. Regardless, these autonomous vehicles are prone to GPS signal loss in urban environments due to obstructions that cause scintillation, multi-path, and shadowing. These effects that decrease the GPS functionality can deteriorate the accuracy of GPS positioning causing losses in signal tracking leading to a decrease in navigation performance. These effects are modeled into the simulation environment and are used as part of the path planning algorithm to provide better navigation …

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …

Assessing High Dynamic Range Imagery Performance For Object Detection In Maritime Environments, Erasmo Landaeta

Doctoral Dissertations and Master's Theses

The field of autonomous robotics has benefited from the implementation of convolutional neural networks in vision-based situational awareness. These strategies help identify surface obstacles and nearby vessels. This study proposes the introduction of high dynamic range cameras on autonomous surface vessels because these cameras capture images at different levels of exposure revealing more detail than fixed exposure cameras. To see if this introduction will be beneficial for autonomous vessels this research will create a dataset of labeled high dynamic range images and single exposure images, then train object detection networks with these datasets to compare the performance of these networks. …

Neural Network Fusion Of Multi-Modal Sensor Data For Autonomous Surface Vessels, David J. Thompson

Doctoral Dissertations and Master's Theses

Autonomous surface vessels (ASV) can potentially improve the safety of vessels traditionally operated by humans. Despite advancements in autonomous on-road vehicles, many of these advancements have yet to be realized for ASVs. This is primarily due to lacking ASV sensing platforms and public datasets for ASV-based perception research. To that end, this dissertation demonstrates the design of a synchronized multi-modal sensing platform for ASVs utilizing GPS/INS, LiDAR, LWIR cameras, HDR camera, and high-resolution cameras. The sensing platform is designed to maximize the overlap of sensors for multi-modal research and provides accurate intrinsic and extrinsic calibration between each sensor. Furthermore, the …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …

Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs, James Hendrickson

Doctoral Dissertations and Master's Theses

The sector of maritime robotics has seen a boom in operations in areas such as surveying and mapping, clean-up, inspections, search and rescue, law enforcement, and national defense. As this sector has continued to grow, there has been an increased need for single unmanned systems to be able to undertake more complex and greater numbers of tasks. As the maritime domain can be particularly difficult for autonomous vehicles to operate in due to the partially defined nature of the environment, it is crucial that a method exists which is capable of dynamically accomplishing tasks within this operational domain. By considering …

A Comprehensive Mapping And Real-World Evaluation Of Multi-Object Tracking On Automated Vehicles, Alexander Bassett

Doctoral Dissertations and Master's Theses

Multi-Object Tracking (MOT) is a field critical to Automated Vehicle (AV) perception systems. However, it is large, complex, spans research fields, and lacks resources for integration with real sensors and implementation on AVs. Factors such those make it difficult for new researchers and practitioners to enter the field.

This thesis presents two main contributions: 1) a comprehensive mapping for the field of Multi-Object Trackers (MOTs) with a specific focus towards Automated Vehicles (AVs) and 2) a real-world evaluation of an MOT developed and tuned using COTS (Commercial Off-The-Shelf) software toolsets. The first contribution aims to give a comprehensive overview of …

Dynamics And Control Of Higher-Order Nonholonomic Systems, Jaime Rubio HerváS

Doctoral Dissertations and Master's Theses

A theoretical framework is established for the control of higher-order nonholonomic systems, defined as systems that satisfy higher-order nonintegrable constraints. A model for such systems is developed in terms of differential-algebraic equations defined on a higher-order tangent bundle. A number of control-theoretic properties such as nonintegrability, controllability, and stabilizability are presented. Higher-order nonholonomic systems are shown to be strongly accessible and, under certain conditions, small time locally controllable at any equilibrium. There are important examples of higher-order nonholonomic systems that are asymptotically stabilizable via smooth feedback, including space vehicles with multiple slosh modes and Prismatic-Prismatic-Revolute (PPR) robots moving open liquid …

Nonlinear Control For Dual Quaternion Systems, William D. Price

Doctoral Dissertations and Master's Theses

The motion of rigid bodies includes three degrees of freedom (DOF) for rotation, generally referred to as roll, pitch and yaw, and 3 DOF for translation, generally described as motion along the x, y and z axis, for a total of 6 DOF. Many complex mechanical systems exhibit this type of motion, with constraints, such as complex humanoid robotic systems, multiple ground vehicles, unmanned aerial vehicles (UAVs), multiple spacecraft vehicles, and even quantum mechanical systems. These motions historically have been analyzed independently, with separate control algorithms being developed for rotation and translation. The goal of this research is to study …