<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">The emergence of Autonomous Mobile Robots (AMR) signifies a pivotal shift in vehicle-based material handling systems, demonstrating their effectiveness across a broad spectrum of applications. Advancing beyond the traditional Automated Guided Vehicles (AGV), AMRs offer unprecedented flexibility in movement, liberated from electromagnetic guidance constraints. Their decentralized control architecture not only enables remarkable scalability but also fortifies system resilience through advanced conflict resolution mechanisms. Nevertheless, transitioning from AGV to AMR presents intricate challenges, chiefly due to the expanded complexity in path planning and task selection, compounded by the heightened potential for conflicts from their dynamic interaction capabilities. This dissertation confronts these challenges by fully leveraging the technological advancements of AMRs. A kinematic-enabled agent-based simulator was developed to replicate AMR system behavior, enabling detailed analysis of fleet dynamics and interactions within AMR intralogistics systems and their environments. Additionally, a comprehensive fleet management protocol was formulated to enhance the throughput of AMR-based intralogistics systems from an integrated perspective. A pivotal discovery of this research is the inadequacy of existing path planning protocols to provide reliable plans throughout their execution, leading to task allocation decisions based on inaccurate plan information and resulting in false optimality. In response, a novel machine learning enhanced probabilistic Multi-Robot Path Planning (MRPP) protocol was introduced to ensure the generation of dependable path plans, laying a solid foundation for task allocation decisions. The contributions of this dissertation, including the kinematic-enabled simulator, the fleet management protocol, and the MRPP protocol, are intended to pave the way for practical enhancements in autonomous vehicle-based material handling systems, fostering the development of solutions that are both innovative and applicable in industrial practices.<br></p>

<p dir="ltr">Over 150,000 people undergo lower-extremity amputations yearly in the United States. In recent years, multiple efforts have been made to improve the human-robot interaction between amputees and active lower limb prostheses. Using lightweight wearable technologies has been a viable solution to implement algorithms that can estimate gait kinematics and prosthesis users’ intent. Examples of wearable technologies include inertial measurement units, strain gauges, and electromyography sensors. Kinematic and force data is inputted into an Error-State Kalman filter to estimate the inversion-eversion, external-internal, and dorsiflexion-plantarflexion ankle angle. The filter tracked the ankle angle with an accuracy of 0.7724°, 0.8826°, and 1.3520°, respectively. The gait phase was estimated using a linear regression model based on a shank kinematics ground truth pattern with an average normalized accuracy of 97.79 %. A numerical simulation of a gait emulator in the form of a 3-Revolute-Prismatic-Revolute (3-RPR) manipulator. The gait emulator can test lower limb prostheses independent of human subjects, eliminating many hurdles associated with human subject testing. The manipulator was simulated with two control strategies: a traditional PID and a hybrid PID + Active Force Control controller (AFC). The hybrid PID+AFC provided higher accuracy in tracking the desired end-effector trajectory due to improved disturbance rejection. A low-cost surface electromyography (sEMG) platform was developed to robustly acquire sEMG signals, with an overall component cost of 35.06 US$. The sEMG platform integrates directly into a Micro:bit microcontroller through an expansion board. During testing with human subjects, sEMG Micro:bit platform had a reported average signal-to-noise ratio of 24.7 dB.</p>

<p>One of the most often utilized machinery in fluid power applications is the material-handling machines, which includes telehandlers, forklifts, cranes, and scissor lifts that are used from constructions to mining.<br> Counterbalance valves (CBVs), hydraulic components that protect the system from failures and manage the load under overrunning load conditions due to their distinctive design, are used in material-handling devices to ensure both the operators' and most off-road vehicles' safety. However, they present a significant shortcoming: the over-pressurization of the supply line, which leads to constringent energy consumption. The primary motivation for this work is this drawback. In this work, a CBV-based system with an adjustable pilot has been investigated using a truck-mounted hydraulic crane as a reference machine.</p> <p>By analyzing theoretically and experimentally the behavior of this novel hydraulic system, it is possible to achieve up to 90% of energy-saving than a baseline configuration of a load-holding machine by controlling the opening of the CBV by adjusting the pressure at the pilot stage. After exploring the capabilities of the studied system and the possible control strategies to control opening of the CBV, this work suggests two different solutions to control the system: “Smart CBV” and “Smart System” modes. By properly controlling the signal on the pilot stage of the CBV, "Smart CBV" enables energy savings of up to 80%. On the other hand, the "Smart System" mode can save up to 95% of energy by using the CBV as a meter-out element that successfully regulates the flow to the actuator and, consequently, its velocity. To attain these outstanding results, it is essential to maintain proper system control.</p> <p>Moreover, since safety is one of the priorities of this type of machine, a Condition Monitoring (CM) model is developed to ensure the actual functionalities of the novel proposed system. By identifying faulty conditions and preventing breakdowns before they occur, CM can be utilized to improve the safety of these type of machines. However, training a CM model using experimental data is time-consuming and expensive since it requires abundant data with different extent of machine failures from the field test. The solution suggested in this work is to generate faulty and healthy data for the reference machine using a high-fidelity simulation tool to train a CM model.</p> <p>Particular focus is given to the counterbalance valve (CBV), a crucial element for the hydraulic system of material handling machines, and the linear actuator (hydraulic cylinder). The different types of faults on two elements are modeled with an approach validated using experimental tests. Considering that the simulation model provides comparable outcomes to training on empirical data, the CM model is trained in a single fault condition and multi faults conditions using simulated data. Instead, the CM model is tested using the experimental tests in multiple faulty conditions on the chosen components.</p> <p>Moreover, finding the best CM model for this case study is another goal of this work. As a result, several CM models are investigated: Random Forest (RF), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). In terms of precision and recall, metrics frequently employed in the CM field to assess the performances of the designed CM model, the results generally indicate more than 90% accuracy.</p>

Ces travaux portent sur la conception multidisciplinaire de systèmes intégrés. Ces systèmes sont soumis à un nombre d’exigences toujours croissant, entraînant des besoins en termes d’intégration fonctionnelle et spatiale. Ces différents types d’intégration relative au produit sont également la source d’une complexité organisationnelle, provenant à la fois de la multitude d’acteurs réalisant différentes activités d’ingénierie, mais également de la diversité des domaines impliqués, désignée dans ce manuscrit par « intégration multidisciplinaire ». Pour favoriser cette intégration multidisciplinaire, les phases de « conception préliminaire » et de « conception détaillée » ont été identifiées comme déterminantes, notamment car elles se caractérisent par la collaboration de nombreux experts, manipulant un grand nombre de données techniques de définition. Les systèmes conçus lors de conceptions multidisciplinaires restent faiblement intégrés. Cela est en partie dû au cloisonnement entre les disciplines et à un mode d’organisation projet basé sur une planification prédominante, caractérisé notamment par une diffusion de l’information principalement descendante (top-down). Afin d’assurer une meilleure collaboration entre ces différentes disciplines, de permettre des prises de décision éclairées par des indicateurs opérationnels et de pouvoir analyser et mieux comprendre les phénomènes d’intégration des expertises, l’introduction d’une méthode inspirée des principes fondateurs des méthodes agiles est proposée pour la conception collaborative de systèmes intégrés.La contribution de ces travaux s’appuie sur trois concepts complémentaires. Le premier, intitulé Collaborative Actions Framework correspond à un cadre de collaboration opérationnelle autour d’actions. Un des objectifs de ce framework est de faciliter la collaboration des acteurs des projets de conception, quelle que soit leur origine disciplinaire, mais également d’assurer une traçabilité entre les prises de décision et les corrections/modifications apportées sur les données techniques. Cette traçabilité est rendue possible grâce aux liens existants avec le second concept intitulé Workspace. Apportant un nouvel éclairage sur les possibilités offertes par la collaboration autour de ces espaces de collaboration, ce concept offre un certain nombre de possibilités,notamment la mise en commun continue des travaux, l’intégration multidisciplinaire et la validation des modifications. Les échanges de données techniques entre les workspaces, ou le travail simultané sur les mêmes données techniques, s’appuient quant à eux sur la possibilité de pouvoir gérer de façon parallèle différentes versions d’une même donnée technique. Ces possibilités sont proposées par le troisième concept, intitulé branch & merge, qui permet également à différents acteurs de travailler simultanément sur les mêmes données. Enfin, ces trois concepts sont ensuite illustrés par l’intermédiaire d’un démonstrateur composé d’un scénario et d’un prototype informatique. Un produit mécatronique, combinaison synergique et systémique de la mécanique, de l'électronique et de l'informatique temps réel, est utilisé afin d’illustrer les possibilités offertes par nos travaux en termes d'intégration multidisciplinaire lors de la conception collaborative. / This work focuses on the multidisciplinary and collaborative design of integrated systems. These systems are subject to an ever increasing number of requirements, leading to the need for more comprehensive functional and spatial integration. These different types of product integration are also at the origin of organizational complexity. This complexity arises not only from the great number of actors performing various engineering activities but also from the diversity of disciplines involved (designated in this manuscript as “multidisciplinary integration”). To encourage this multidisciplinary integration, “preliminary design” and “detailed design” have been identified as the most significant steps, especially since they are characterized by the collaboration of multiple experts handling a large number of product definition’ technical data. Systems that have been designed thanks to multidisciplinary approaches are generally poorly integrated. This is partially due to the compartmentalization of disciplines, as well as to the “project-planned” method, where project planning is predominant and information is mainly spread out “top-down”. To ensure better cooperation between the various disciplines, to enable decision making based on operational indicators and to analyze and understand the multidisciplinary integration processes, a method inspired by the founding principles of agile methods (the agile manifesto) is proposed for the collaborative design of integrated systems. This work is based on three complementary concepts. The first is, the Collaborative Actions Framework, an operational framework for collaboration around actions. One objective of this framework is to improve the collaboration among designers, whatever their disciplinary origin. It also ensures traceability between decision making and corrections/changes made to technical data. This traceability is made possible by the useof the second concept, called Workspace. Even if this term is already well known, we propose a new definition/usage to transform it into collaboration spaces. This concept offers great possibilities, including the continuous delivering/sharing of experts’ contributions, multidisciplinary integration and change validation. The exchange of technical data between workspaces, or simultaneous work on the same data, relies on the ability to manage several parallel versions of the same item into a single datamanagement system. These opportunities are offered by the third concept, called Branch & Merge. Finally, these three concepts are illustrated through a scenario and a computer prototype. A mechatronic product, “the synergistic combination of mechanical and electrical engineering, computer science, and information technology” (Harashima et al., 1996), is used to illustrate the opportunities offered by our work in terms of multidisciplinary integration during collaborative design.

<p>The purpose of this research experiment was to explore and implement a cost-effective automation solution into a low volume production line for loading parts onto a coordinate measuring machine (CMM) for dimensional inspection. Quality control practices have historically been separated from production process by inspection routines being performed in a controlled lab. The system demonstrated the possibilities of an in-process automation of the quality control process that was feasible to be implemented for small and mid-sized manufacturing companies. The process involved an APSX horizontal injection mold machine dispensing parts onto the conveyor belt. The conveyor belt was controlled by a Phoenix Contact PLC and two line sensors that provided two stopping point for cooldown before inspection. A MyCobot 320-M5 robotic arm was used to select the part off the line and places it into a fixture on a Hexagon coordinate measuring machine (CMM).</p>

<p dir="ltr">The growing movement toward sustainable use of ocean resources is driven by the pressing need to alleviate environmental and human stressors on the planet and its oceans. From monitoring the food web to supporting sustainable fisheries and observing environmental shifts to protect against the effects of climate change, ocean observations significantly impact the Blue Economy. Acknowledging the critical role of Autonomous Underwater Vehicles (AUVs) in achieving persistent ocean exploration, this research addresses challenges focusing on the limited energy and storage capacity of AUVs, introducing a comprehensive underwater docking solution with a specific emphasis on enhancing the terminal homing phase through innovative vision algorithms leveraging neural networks.</p><p dir="ltr">The primary goal of this work is to establish a docking procedure that is failure-tolerant, scalable, and systematically validated across diverse environmental conditions. To fulfill this objective, a robust dock detection mechanism has been developed that ensures the resilience of the docking procedure through \comment{an} improved detection in different challenging environmental conditions. Additionally, the study addresses the prevalent issue of data sparsity in the marine domain by artificially generating data using CycleGAN and Artistic Style Transfer. These approaches effectively provide sufficient data for the docking detection algorithm, improving the localization of the docking station.</p><p dir="ltr">Furthermore, this work introduces methods to compress the learned docking detection model without compromising performance, enhancing the efficiency of the overall system. Alongside these advancements, a station-keeping algorithm is presented, enabling the mobile docking station to maintain position and heading while awaiting the arrival of the AUV. To leverage the sensors onboard and to take advantage of the computational resources to their fullest extent, this research has demonstrated the feasibility of simultaneously learning docking detection and marine wildlife classification through multi-task and transfer learning. This multifaceted approach not only tackles the limitations of AUVs' energy and storage capacity but also contributes to the robustness, scalability, and systematic validation of underwater docking procedures, aligning with the broader goals of sustainable ocean exploration and the blue economy.</p>

Les machines électriques jouent un rôle très important dans la conversion d'énergie dans plusieurs applications et domaines. Les contraintes thermiques jouent ainsi un rôle indispensable dans la conception des machines électriques de plus en plus petites et performantes. En effet, la performance des machines électriques est limitée par les températures maximales admissibles dans certaines zones critiques telles que le bobinage, les aimants permanents et les roulements. Deux approches principales peuvent être utilisées pour étudier le comportement thermique de la machine: la méthode nodale ou le circuit à constantes localisées ou les modèles numériques. Dans notre étude, nous proposons d'appliquer la méthode nodale sur une machine électrique intégrée dans un environnement mécatronique complexe. Le modèle thermique développé de la machine est ainsi présenté avec ses différents éléments. En effet, un modèle précis dépend fortement de plusieurs paramètres thermiques tels que les coefficients d'échange convectif, les conductances de contact, les conductivités équivalentes du bobinage, et autres paramètres. En conséquence, des techniques d'analyse de sensibilité sont ensuite appliquées sur le modèle thermique pour identifier les paramètres d'influence significative sur les températures de la machine ainsi que pour la réduction de ce modèle. Ensuite, nous appliquons deux méthodologies d'identification des paramètres thermiques incertains sont développées et appliquées afin de recaler le modèle thermique de la machine. Cette étape permet la validation de ce modèle par rapport à des mesures thermiques sur une machine synchrone à aimants permanents internes installée sur un banc de caractérisation de machine électriques. Finalement, nous intégrons le modèle recalé dans une approche système mécatronique comportant les lois de commande de la machine ainsi que son convertisseur. Ceci permettra ainsi d'étudier l'influence de la température d'une machine électrique sur le système mécatronique complet. / Electric machines play an important role in power conversion in several applications and fields. With the increasing demand for designing lighter and more efficient machines and optimizing the existing structures, thermal analysis becomes a necessary; in fact, the performance of electric machines islimited by the allowable temperatures in many critical components like windings, permanent magnetsand bearings. Two main approaches can be employed in order to study the machine thermal behavior : the lumped parameter thermal network (LPTN) or numerical models. Considering low-computationtime-consuming and the possibility to be integrated in a mechatronics system design, the LPTN method is considered in our study. The latter is mainly applied on electric machine integrated in a complex mechatronics environment. The thermal network is presented along with the definition of the principal elements constituting this network. In fact, an accurate and reliable network strongly depends on many critical parameters like heat transfer coefficients, interface gaps, impregnation goodness, among others. For this reason, different sensitivity analysis techniques are carried out in order to, first, identify the significance of uncertainties in the evaluation of these parameters on machine temperatures and second, to reduce the thermal network. Next, we propose two optimization algorithm-based identification methodologies in order to calibrate results of the thermal network with measured temperatures obtained from a test-bench of a permanent magnet based integrated starter-generator machine. The calibrated model is then integrated in a mechatronics system consisting of an electric model of the electric machine, along with its control strategy and the power converter. This final study allows us to evaluate the impact of the machine temperature rise on the mechatronic system.

<p>The "Maker Movement" is a cultural phenomena rooted in DIY culture, which stresses making devices and creations on your own rather than purchasing it ready-made. At the core of the Maker Movement, is the "Maker Mindset"; a collection of attitudes, beliefs and behaviors that emphasize the importance of creativity, experimentation and innovation in the learning process. Since the Maker Mindset embodies constructionist principles at its core that push makers to experiment and problem-solve by collaborating with fellow makers through hands-on activities, it can be said that these activities comprise of Creative, Learning and Collaborative experiences. While Internet-of-Things devices have long been used to enhance these activities, research pertaining to using Augmented Reality in tandem with IoT for the purpose of enhancing experiences core to the Maker Mindset is relatively unexplored. Three different systems were developed with the goal of addressing this -- MicrokARts, ShARed IoT and MechARspace. Each system focuses on enhancing one of the three core experiences through AR-compatible IoT devices, whilst ensuring that they do not require prerequisite knowledge in order to author AR experiences. These systems were evaluated through user studies and testing over a variety of age-groups, with each system successfully enhancing one core experience each through the use of AR-IoT interactions.</p>