Navigation, Guidance, Control, and Dynamics Commons^™

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Adaptive – Compositional Method For Coordinating Subsystems At Different Levels In Hierarchical Control Systems, Husan Zakirovich Igamberdiyev, Uktam Farxodovich Mamirov Mr, Inomjon Ilxom Ugli Abdukaxxarov Mr

Technical science and innovation

This paper examines the problem of synthesizing algorithms for the composition of subsystems at various levels within complex hierarchical control systems under conditions of uncertainty and resource constraints. It is demonstrated that classical composition algorithms, which rely on the intersection of admissible sets and the use of local optimality criteria, suffer from several significant drawbacks. These include a combinatorial increase in complexity, dependence on the expert selection of parameters, and limited applicability in dynamic environments. To overcome these shortcomings, an adaptive-compositional method is proposed. This method is based on the dynamic recalculation of coordination parameters, the integration of model predictive …

A Comparative Study Of Model Predictive Control And The Stanley Method For Vehicle Path Tracking Applications, Noah S. Fitzgerald

Master's Theses

This thesis compares a model predictive controller (MPC) and a lateral Stanley controller for vehicle path-tracking applications under simulation-based and perception-driven operating conditions. Both controllers were evaluated in simulation using a nonlinear dynamic bicycle model executing single and double lane change maneuvers. Following simulation-based evaluation, both controllers were implemented on hardware within a perception-driven steering-control pipeline. This pipeline utilized recorded sensor data from the MXcarkit 1/8^th-scale autonomous vehicle platform, incorporating lane instance segmentation and homography-based roadway estimation.

Under idealized simulation conditions, the MPC demonstrated improved trajectory-tracking performance during aggressive maneuvers while requiring greater steering activity and computational effort …

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …

Multi-Level Energy Optimization For Connected And Automated Vehicles: From Cooperative Multi-Vehicle Control To Individual Powertrain Management, Pruthwiraj Santhosh

Dissertations, Master's Theses and Master's Reports

The transportation sector currently accounts for nearly 30% of global energy consumption, necessitating urgent advancements in vehicle efficiency to meet Net Zero targets. Leveraging connectivity and automation, this dissertation proposes and validates methodologies to reduce the energy consumption of light-duty vehicles at both fleet and individual levels.

First, a validation framework is developed to bridge the “simulation-to-real world” gap in Cooperative Automated Vehicle (CAV) research. Moving beyond virtual simulations, the study establishes a methodology for physically validating centralized control architectures via a custom Cellular V2X network. By synchronizing vehicle-powertrain models with physical test vehicles, the framework successfully orchestrates complex arterial …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold

Dartmouth College Ph.D Dissertations

Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …

Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System, Dimitry Melnikov, Evan Bartel, Andrew Burrier, Goran Gjorgievski

Williams Honors College, Honors Research Projects

NASA's Artemis program requires precise navigation capabilities to establish the first sustained presence on the lunar surface. However, as launches bring necessary orbital infrastructure, the Artemis program will face a critical period during which reliable lunar navigation is not possible. To address this challenge, the V.E.C.T.O.R. system tracks assets, such as rovers and astronauts, as User Terminals relative to a pre-existing cell tower, or Base Station. To do so, the system leverages existing Base Station hardware to calculate the location of User Terminals in conjunction with existing communications infrastructure.

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

Capacitive Sensors With Ultra-Small Capacitance For Smart Measurement And Control Systems, Rustam Baratov, Farrux Jabbor O'G'Li Ko'charov

Chemical Technology, Control and Management

This article discusses methods of low capacitance measurement of capacitive sensors. The results of the study of the amplitude-frequency (AF) and phase-frequency (PF) response of measurement circuits of capacitive sensors for low capacitances measurement, consisting of RC - differentiating elements are presented. The input and output parameters of the differentiating circuit and the complex transfer function are analyzed. The research results show that low capacitances measurement by measuring the rectangular pulses duration is the most effective measurement method.

Autonomous Apple Harvester Robot, Jack Ryan Cline, Tyus Green, Devon Woolston

Electrical Engineering

As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location …

V2i-Based Adaptive Collision Avoidance For Safety And Traffic Efficiency, Vaishnavi Balambeed

Dissertations, Master's Theses and Master's Reports

To leverage the growing communication and connectivity among modern vehicles, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) systems are increasingly being used to implement active safety applications. However, current research often overlooks the impact of algorithms such as collision avoidance on traffic flow efficiency. This work investigates the adaptation of a collision avoidance algorithm implemented in V2I to incorporate a variable time headway and spacing control strategy. The proposed approach aims to maintain higher average speeds among vehicles, lower individual vehicle’s waiting, and travel times in the vicinity of the infrastructural unit while simultaneously avoiding collisions; thereby enhancing both safety and traffic …

Extending Trailer, Alex Grove

Williams Honors College, Honors Research Projects

The goal of this research project is to revolutionize the convenience in towable transportation. This innovative design aims to enhance the versatility of pull-behind trailers by incorporating an extendable feature, allowing users to effortlessly adjust the length according to their specific needs. Whether navigating tight spaces or accommodating extra cargo, our trailer adapts to diverse situations, providing unmatched flexibility. In addition to its adjustable length, the trailer is engineered to be compactable, addressing the storage constraints often faced by users with limited space. The collapsible design ensures easy storage without compromising on functionality, making it an ideal solution for individuals …

Adaptive Traction, Power And Torque Control Strategies And Optimization In An All-Electric Powertrain, Aymane Hidara

Theses and Dissertations

Electric and hybrid-electric vehicles lean heavily on intricate control algorithms to provide smooth, reliable, and secure operations under any driving conditions. Three distinct supervisory control strategies have been developed, each aiming to improve reliability and vehicle performance of a dual-motor electric vehicle equipped with an all-wheel-drive, fully electric powertrain. These algorithms are adept at dynamically modulating and constraining the torque provided to the wheels, leveraging two autonomous permanent magnet electric drive units. This study utilizes a vehicle model jointly provided by MathWorks and General Motors in partnership with industry sponsors. The these strategies were implemented in the model and enhanced …

Traffic Light Detection And V2i Communications Of An Autonomous Vehicle With The Traffic Light For An Effective Intersection Navigation Using Mavs Simulation, Mahfuzur Rahman

Theses and Dissertations

Intersection Navigation plays a significant role in autonomous vehicle operation. This paper focuses on enhancing autonomous vehicle intersection navigation through advanced computer vision and Vehicle-to-Infrastructure (V2I) communication systems. The research unfolds in two phases. In the first phase, an approach utilizing YOLOv8s is proposed for precise traffic light detection and recognition, trained on the Small-Scale Traffic Light Dataset (S2TLD). The second phase establishes seamless connectivity between autonomous vehicles and traffic lights in a simulated Mississippi State University Autonomous Vehicle Simulation (MAVS) environment resembling a small city with multiple intersections. This V2I system enables the transmission of Signal Phase and Timing …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

Mathematical Model Of An Industrial Robot Built On The Basis Of Linear Motion Mechatron Modules, Matyokubov Nurbek Rustamovich, Rakhimov Temurbek Omonboyevich

Chemical Technology, Control and Management

The use of Industry 4.0 technologies in modern production serves to increase production efficiency. Robots and robotic complexes with innovative intelligent control are widely used in industrial production. However, studying their mechanical part, linear motion mechatronic modules and control system is a complex object. The variety and complexity of control methods and operating modes negatively affects the operator's working time and production productivity. In such cases, it is necessary to improve control methods and develop technologies used in industry, including robots and robotic manipulators, which allow to perform short movements with high accuracy and speed. In the article, the mathematical …

Integrated Energy-Aware Motion Planning And Charge Scheduling Of Unmanned Aerial Vehicles, Hayleyesus Alemayehu

All Theses

The growing demand for unmanned aerial vehicles (UAVs) is driven by their operational convenience, cost-effectiveness, availability, and adaptability to various scenarios. In energy-constrained environments, optimizing energy consumption and ensuring a continuous power supply for UAVs is crucial for mission success. The objective of this thesis is to address this issue by integrating energy-aware motion planning and charge scheduling for UAVs by utilizing a charger hosted on an unmanned ground vehicle (UGV), whose rendezvous locations and routes are jointly computed to minimize overall energy consumption.

This thesis proposes a hierarchical trajectory and control framework comprising local and global planners for each …

Improved Vehicle-Bridge Interaction Modeling And Automation Of Bridge System Identification Techniques, Omar Abuodeh

All Dissertations

The Federal Highway Administration (FHWA) recognizes the necessity for cost-effective and practical system identification (SI) techniques within structural health monitoring (SHM) frameworks for asset management applications. Indirect health monitoring (IHM), a promising SHM approach, utilizes accelerometer-equipped vehicles to measure bridge modal properties (e.g., natural frequencies, damping ratios, mode shapes) through bridge vibration data to assess the bridge's condition. However, engineers and researchers often encounter noise from road roughness, environmental factors, and vehicular components in collected vehicle signals. This noise contaminates the vehicle signal with spurious modes corresponding to stochastic frequencies, impacting damage monitoring assessments. Thus, an efficient and reliable SI …

Topological Interpolation Method For Modeling Dynamic Systems, Isamiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Chemical Technology, Control and Management

The method of simulation structural-complex continuous-discrete control systems is discussed. For simulation and calculation of dynamic processes in continuous-discrete systems topological interpolation method is proposed, based on application of hybrid methods of space of state variables and interpolation of signals. The essence of the method is that the dynamics of the investigated system, considered at the final interval, is broken down into subintervals, on each of which the processes are described by linear ordinary system differential equations. The computational efficiency of the proposed method was evaluated by comparison with standard methods such as the Runge-Kutta-Merson method. The use of this …

Sensor Updates For Bigheaded Carp-Tracking Autonomous Boat, Jordan Kaufmann

Honors College Theses

Bigheaded carp are an invasive species that overpopulate and compete with the native species of Kentucky Lake as well as many other North American aquatic ecosystems. The movement patterns of Bigheaded carp are being studied nationwide by the United States Geological Survey and multiple universities. These studies ultimately seek to control their spread and reduce or reverse the ecosystem destabilization caused by this invasive species. Such studies are currently conducted manually on Kentucky Lake by graduate students affiliated with the Murray State University (MSU) Biology Department and Hancock Biological Station, and these manual studies are an arduous and time-consuming effort. …

Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi

All Dissertations

Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …

Control And Optimization Of Multi-Agent Systems With Applications In Connected And Autonomous Electric Vehicles, Shaopan Guo

LSU Doctoral Dissertations

A multi-agent system (MAS) is a system in which multiple autonomous agents interact with each other to achieve a common goal. Nevertheless, current designs of MAS controllers typically rely on particular requirements, such as time-triggered communication, linear dynamics, and access to global information. These limitations restrict the applicability of MASs. This thesis aims to eliminate these constraints and optimize the energy consumption of a specific MAS, namely connected autonomous electric vehicles (CAEVs).

This thesis first addresses the consensus problem of linear MASs with intermittent communication. An adaptive distributed control algorithm that integrates edge-based event-triggered (ET) communication mechanisms is presented in …

View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images or Google Street Views. However, the problem remains challenging due to the inconsistency between the query images and the large-scale reference datasets regarding various light and weather conditions. To tackle this issue, this work proposes a novel view synthesis framework equipped with deep generative models, which can merge the unique features from the outdated reference dataset with …

Study Of Eco-Driving And Charging Planning In Connected And Automated Vehicles Environment, Pradeep Bhat

Dissertations, Master's Theses and Master's Reports

In this dissertation, the development of eco-driving and charging planning algorithms in the connected and automated vehicle environment (CAV) are presented. CAV technologies provide opportunities for potential energy savings and efficiency improvement of transportation networks, which are explored through multiple research tasks in this study.

The objective of the first study presented in Chapter 2 is to reduce vehicle dynamic losses and required tractive force while completing trip distance within a given travel time. Sequential Quadratic Programming method is employed for this nonlinearly constrained optimization problem. The validation result illustrates the benefits of optimal velocity trajectories. The objective of the …

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

College of Graduate Studies: Theses & Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …

On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation, Eduardo Morillo

Doctoral Dissertations and Master's Theses

The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system's flight envelop and trajectory following. This thesis focuses on …

Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng

All Dissertations

Multi-robot systems (MRS) can accomplish more complex tasks with two or more robots and have produced a broad set of applications. The presence of a human operator in an MRS can guarantee the safety of the task performing, but the human operators can be subject to heavier stress and cognitive workload in collaboration with the MRS than the single robot. It is significant for the MRS to have the provable correct task and motion planning solution for a complex task. That can reduce the human workload during supervising the task and improve the reliability of human-MRS collaboration. This dissertation relies …