<p dir="ltr">A fluid extraction device designed to extract bands of fluid from an ultracentrifuged vial was developed. To do this, a computer vision system was developed to scan the vial and detect the bands and calculate their positions. The computer vision was performed using a TSL1401 DB linescan camera. The vial was scanned by moving the vial vertically in front of the camera using a stepper motor driven linear stage. Pixel data from the line scan camera was analysed to find the edges of each band. This was done by analyzing the first and second derivatives of smoothed pixel data. When the second derivative was 0 and the first derivative was greater than a threshold value, a band edge was detected. Needles were connected to linear actuators and were used to puncture the vials at the desired band's position. After puncturing the vial, fluid was extracted from the vials using a peristaltic pump and placed in a reservoir. Several control architectures were tested an used to control the system. The final control architecture used a LattePanda miniPC to control the system. Several iterations of the fluid extraction device were also created, with the final iteration meeting all the requirements for the device.</p>

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<p>Precision livestock farming (PLF) has emerged as a solution to address global challenges related to food scarcity, increasing demand for animal products, slim profit margins in livestock production, and growing societal concerns regarding farm animal welfare. By offering individualized care for animals, PLF aims to provide labor savings, enhanced monitoring, and improved control capabilities within complex farming systems, enabled by digital technologies. The adoption of an individual-centric approach to farming through PLF is anticipated to enhance farm productivity and ensure ethical treatment of animals while mitigating concerns associated with labor shortages in modern intensive farming operations. Real-time continuous monitoring of each animal enables precise and accurate health and well-being management. However, to achieve these benefits, large-scale animal farms require commercially viable technological solutions for individualized care and welfare. Cyber-physical systems (CPSs) offer precise monitoring and control and present a promising avenue for PLF but pose significant implementation challenges.</p> <p>  In this work, a generalizable CPS architecture was formalized with active robotic nodes that can realize adaptive continuous real-time animal health monitoring to maximize productivity, animal welfare, and sustainability. Taking the example of dairy farming, a resource- and criticality-aware CPS was developed that enables real-time resource-aware sensing, adaptive control, and agile networking with an emphasis on handling emergencies autonomously. Using a decentralized approach, each node was made capable of optimizing its operation to be resource conscious, while also being able to identify emergency conditions in real-time. In this novel design, we accommodate the social dynamics of the herd and effectively address the various types of emergencies possible in PLF. Moreover, the communication was customized for the unique needs of animal agriculture, wherein it reduced latency and power consumption while ensuring collision-free two-way synchronization with adaptive range extension for emergency conditions. Further, since the CPS was centered around animals, a special robust security layer was also developed and implemented to protect the active embodied nodes against known and unknown malicious attacks. The proposed CPS reference architecture provides a foundation for implementing individualized care and welfare, ultimately improving the efficiency and sustainability of livestock operations.</p>

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<p>Cyber-physical systems (CPS) are a class of complicated systems integrating cyber components with physical components. Although such a cyber-physical interaction improves the system performance and intelligence, it increases the system complexity and makes the system vulnerable to various types of faults, failures, and cyber-attacks. To assure the security and improve the resiliency of CPS, it is found that the hybrid system model can be a powerful tool in the domain of fault detection and isolation, cyber-attack diagnosis and containment, as well as resilient control and reconfiguration. Several problems are concerned in this dissertation. For situational awareness, \textit{mode discernibility}, which stands for whether the discrete state of a hybrid system can be correctly identified, is characterized and discussed with potential applications to monitoring system design. For CPS vulnerability analysis, the problem of stealthy attack design for systems with switching structures is investigated, which is motivated by the recent literature. To further understand and remedy for the vulnerabilities, the detectability and identifiability for severe cyber-attacks are defined and characterized, which are followed by the discussions on the methodologies for cyber-attack detection and identification. Last but not least, based on the understanding of identifiability, a framework of resilient control design is proposed to mitigate the impact of cyber-attacks, which can be generalized in future to account for additional design criteria.</p>

<p dir="ltr">This research project aims to develop a robotic platform capable of drilling horizontal laterals from existing wellbores, offering data-guided steering and control features using information captured by sensors. The project provides an opportunity to expand the application of downhole drilling robots toward semi-autonomous operations in existing fields, especially those with declining production. Mature fields represent a global resource, and even modest hydrocarbon reserves additions are substantial to keep up the energy demand, having positive economic and environmental impacts. Available lateral drilling techniques do not fit the constraints offered by the challenge; moreover, they are not cost-effective.</p><p dir="ltr">The project will be organized into three phases to accomplish this developmental study. First, design criteria and key performance aspects will be identified and established to design a self-propelled robotic prototype capable of drilling lateral sections from an existing wellbore with an internal diameter of 4” to 6”. The creation of lateral sections can potentially add hydrocarbon reserves taking advantage of an already-drilled vertical section of a mature field. Second, the design of the prototype will take place, along with the design of a sub-surface communication and control system. The third phase is manufacturing and subsystems integration, finishing with a pilot test in a controlled environment. Based on the pilot testing results, design optimization will occur. Finally, a field version will be designed, and IP (Intellectual Property) disclosures and plans for commercialization will be identified and addressed.</p>

<p dir="ltr">Network models are essential for representing a myriad of real-world problems. Two of the most important categories of networks are centralized and distributed networks. In this thesis, we investigate the efficient resource allocation for one centralized communication network and two distributed epidemic networks.</p><p dir="ltr">In Chapter 2, we study three proposed centralized coded caching schemes with uncoded pre-fetching for scenarios where end users are grouped into classes with different file demand sets. We provide a lower bound for the transmission rate for the system with heterogeneous user profiles. Then the transmission rates of the three schemes are compared with the lower bound to evaluate their gap to optimality, and also compared with each other to show that each scheme can outperform the other two when certain conditions are met. Finally, we propose a cache distribution method that results in a minimal peak rate and a minimal average rate for one of the schemes when the users’ storage is relatively small compared with the size of the library.</p><p dir="ltr">In Chapter 3, we examine a discrete-time networked SIR (susceptible-infected-recovered) epidemic model, where the infection, graph, and recovery parameters may be time-varying. We propose a stochastic framework to estimate the system states from observed testing data and provide an analytic expression for the error of the estimation algorithm. We validate some of our assumptions for the stochastic framework with real COVID-19 testing data. We identify the system parameters with the system states from our estimation algorithm. Employing the estimated system states, we provide a novel distributed eradication strategy that guarantees at least exponential convergence to the set of healthy states. We illustrate the results via simulations over northern Indiana, USA.</p><p dir="ltr">In Chapter 4, we propose a novel discrete-time multi-virus SIR model that captures the spread of competing SIR epidemics over a population network. First, we provide a sufficient condition for the infection level of all the viruses over the networked model to converge to zero in exponential time. Second, we propose an observation model which captures the summation of all the viruses’ infection levels in each node, which represents the individuals who are infected by different viruses but share similar symptoms. We present a sufficient condition for the model to be strongly locally observable. We propose a distributed Luenberger observer for the system state estimation. We demonstrate how to calculate the observer gain for the estimator and prove that the estimation error of our proposed estimator converges to zero asymptotically with the observer gain found. We also propose a distributed feedback controller which guarantees that all viruses are eradicated at an exponential rate. We then show via simulations that the estimation error of the Luenberger observer converges to zero before the viruses die out.</p><p dir="ltr">We conclude in Chapter 5, where we summarize the findings of this thesis and introduce several challenging open research questions that arise from its results. These questions encompass a range of topics, including the design of optimal testing strategies for large populations, the investigation of estimation techniques in the presence of noisy measurement models, the extension of the SIR epidemic model to more complex models like SEIR and SAIR, and the exploration of efficient vaccine allocation schemes.</p>

<p>Traditional robots and soft robots have often been treated as two distinct options for design, a dichotomy between stiffness and compliance. In reality, they compose two ends of a spectrum, and there has been research to soften traditional robots and stiffen soft robots. The latter option has seen a large variety of techniques to actively and selectively create stiffness in an otherwise soft robot. The common disadvantage concerning all of them is the need for constant energy input. In this work, a first-of-its-kind method for a permanent stiffness of a growing robot is explored and tested.</p> <p>First, I show the qualitative and quantitative testing of the stiffening method, expanding insulation foam, both by itself and when applied to a vine robot. With this knowledge, I investigate a design to apply the foam to a growing robot as it moves, taking advantage of the properties of the foam to coat a vine robot as needed. This selective foam placement unlocks various unique capabilities like adhering to its environment, imparting & resisting large forces, and isolating sections of its body. Finally, these traits are highlighted in three demonstrations, proving the efficacy of this unique method as well as affirming the utility of permanently stiffening a soft robot. In the future, the work in this thesis can help open the way for permanent deployable robotic structures and soft robots in roles more traditionally used for rigid robots.</p>

<p>Multirotor unmanned aerial vehicles (UAVs) added with the ability to physically interact with the environment has opened endless possibilities for aerial mobile manipulation tasks. With the unlimited reachable workspace and physical interaction capabilities, such robots can enhance human ability to perform dangerous and hard-to-reach tasks. However, realizing aerial mobile manipulation in real-world scenarios is challenging with respect to the diversity in aerial platforms, control fidelity and susceptibility to variations in the environment. Therefore, the first part of the dissertation provides tools to  classify and evaluate different multirotor designs. A measure of responsiveness of a multirotor platform in exerting generalized forces and rejecting disturbances is discussed through the control bandwidth analysis. Superiority in control bandwidth for fully-actuated multirotors is established in a comparison with equivalent under-actuated multirotors. To further classify and distinguish multirotor platforms, a new mobility measure is proposed and compared by surveying all aerial platforms employed for aerial mobile manipulation. In compliance to the control bandwidth analysis, the mobility measure for fully-actuated multirotors is relatively higher making them better suited for manipulation tasks. </p> <p><br></p> <p><br></p> <p>Aerial physical interaction, as a part of aerial mobile manipulation, with partially unknown environments is challenging due to the uncertainties imposed while dexterously exerting force signatures. A hybrid physical interaction (HyPhI) controller is proposed to enable constrained force contact with a steady transition from unconstrained motion, by squelching excess energy during initial impact. However, uncertainties posed by the partially unknown environment requires to understand the surrounding environment and their current physical states, that can enhance interaction performance. The limited resources and flight time of the multirotors requires to simultaneously understand the environment and perform aerial physical interactions. Inspection-on-the-fly is an uncanny ability of humans to intuitively infer states during manipulation while reducing the necessity to conduct inspection and manipulation separately. In this dissertation, the inspection-on-the-fly method based HyPhI controller is proposed to engage in a steady contact with partially unknown environments, while simultaneously estimating the physical states of the surfaces. The proposed method is evaluated in a mockup of real-world facility, to understand the surface properties while engaging in steady interactions. Further, such inspection of surfaces and estimation of various states enables a deeper understanding of the environment while enhancing the ability to physically interact. </p>