Soft pneumatic devices for blood circulation improvement

The research activity I am presenting in this thesis lies within the framework of a cooperation between the University of Cagliari (Applied Mechanics and Robotics lab, headed by professor Andrea Manuello Bertetto, and the research group of physicians referencing to professor Alberto Concu at the Laboratory of Sports Physiology, Department of Medical Sciences), and the Polytechnic of Turin (professor Carlo Ferraresi and his equipe at the Group of Automation and Robotics, Department of Mechanical and Aerospace Engineering) This research was also funded by the Italian Ministry of Research (MIUR – PRIN 2009). My activity has been mainly carried on at the Department of Mechanics, Robotics lab under the supervision of prof. Manuello; I have also spent one year at the Control Lab of the School of Electrical Engineering at Aalto University (Helsinki, Finland). The tests on the patients were taken at the Laboratory of Sports Physiology, Cagliari. I will be describing the design, development and testing of some soft pneumatic flexible devices meant to apply an intermittent massage and to restore blood circulation in lower limbs in order to improve cardiac output and wellness in general. The choice of the actuators, as well as the pneumatic circuits and air distribution system and PLC control patterns will be outlined. The trial run of the devices have been field--‐tested as soon a prototype was ready, so as to tune its features step--‐by--‐ step. I am also giving a characterization of a commercial thin force sensor after briefly reviewing some other type of thin pressure transducer. It has been used to gauge the contact pressure between the actuator and the subject’s skin in order to correlate the level of discomfort to the supply pressure, and to feed this value back to regulate the supply air flow. In order for the massage to be still effective without causing pain or distress or any cutoff to the blood flow, some control objective have been set, consisting in the regulation of the contact force so that it comes to the constant set point smoothly and its value holds constant until unloading occurs. The targets of such mechatronic devices range from paraplegic patients lacking of muscle tone because of their spinal cord damage, to elite endurance athletes needing a circulation booster when resting from practicing after serious injuries leading to bed rest. Encouraging results have been attained for both these two categories, based on the monitored hemodynamic variables

High-Speed Obstacle Avoidance at the Dynamic Limits for Autonomous Ground Vehicles

Enabling autonomy of passenger-size and larger vehicles is becoming increasingly important in both military and commercial applications. For large autonomous ground vehicles (AGVs), the vehicle dynamics are critical to consider to ensure vehicle safety during obstacle avoidance maneuvers especially at high speeds. This research is concerned with large-size high-speed AGVs with high center of gravity that operate in unstructured environments. The term `unstructured' in this context denotes that there are no lanes or traffic rules to follow. No map of the environment is available a priori. The environment is perceived through a planar light detection and ranging sensor. The mission of the AGV is to move from its initial position to a given target position safely and as fast as possible. In this dissertation, a model predictive control (MPC)-based obstacle avoidance algorithm is developed to achieve the objectives through an iterative simultaneous optimization of the path and the corresponding control commands. MPC is chosen because it offers a rigorous and systematic approach for taking vehicle dynamics and safety constraints into account. Firstly, this thesis investigates the level of model fidelity needed for an MPC-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. Five different representations of vehicle dynamics models are considered. It is concluded that the two Degrees-of-Freedom (DoF) representation that accounts for tire nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm to operate the vehicle at its limits within an environment that includes large obstacles. Secondly, existing MPC formulations for passenger vehicles in structured environments do not readily apply to this context. Thus, a novel nonlinear MPC formulation is developed. First, a new cost function formulation is used that aims to find the shortest path to the target position. Second, a region partitioning approach is used in conjunction with a multi-phase optimal control formulation to accommodate the complicated forms of obstacle-free regions from an unstructured environment. Third, the no-wheel-lift-off condition is established offline using a fourteen DoF vehicle dynamics model and is included in the MPC formulation. The formulation can simultaneous optimize both steering angle and reference longitudinal speed commands. Simulation results show that the proposed algorithm is capable of safely exploiting the dynamic limits of the vehicle while navigating the vehicle through sensed obstacles of different size and number. Thirdly, in the algorithm, a model of the vehicle is used explicitly to predict and optimize future actions, but in practice, the model parameter values are not exactly known. It is demonstrated that using nominal parameter values in the algorithm leads to safety issues in about one fourth of the evaluated scenarios with the considered parametric uncertainty distributions. To improve the robustness of the algorithm, a novel double-worst-case formulation is developed. Results from simulations with stratified random scenarios and worst-case scenarios show that the double-worst-case formulation considering both the most likely and less likely worst-case scenarios renders the algorithm robust to all uncertainty realizations tested. The trade-off between the robustness and the task completion performance of the algorithm is also quantified. Finally, in addition to simulation-based validation, preliminary experimental validation is also performed. These results demonstrate that the developed algorithm is promising in terms of its capability of avoiding obstacles. Limitations and potential improvements of the algorithm are discussed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135770/1/ljch_1.pd

Exploring the effects of robotic design on learning and neural control

The ongoing deep learning revolution has allowed computers to outclass humans in various games and perceive features imperceptible to humans during classification tasks. Current machine learning techniques have clearly distinguished themselves in specialized tasks. However, we have yet to see robots capable of performing multiple tasks at an expert level. Most work in this field is focused on the development of more sophisticated learning algorithms for a robot's controller given a largely static and presupposed robotic design. By focusing on the development of robotic bodies, rather than neural controllers, I have discovered that robots can be designed such that they overcome many of the current pitfalls encountered by neural controllers in multitask settings. Through this discovery, I also present novel metrics to explicitly measure the learning ability of a robotic design and its resistance to common problems such as catastrophic interference. Traditionally, the physical robot design requires human engineers to plan every aspect of the system, which is expensive and often relies on human intuition. In contrast, within the field of evolutionary robotics, evolutionary algorithms are used to automatically create optimized designs, however, such designs are often still limited in their ability to perform in a multitask setting. The metrics created and presented here give a novel path to automated design that allow evolved robots to synergize with their controller to improve the computational efficiency of their learning while overcoming catastrophic interference. Overall, this dissertation intimates the ability to automatically design robots that are more general purpose than current robots and that can perform various tasks while requiring less computation.Comment: arXiv admin note: text overlap with arXiv:2008.0639

The use of mechanical redundancy for fault detection in non-stationary machinery

The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.Master's These

Systém pro automatickou kontrolu velikosti a typu ráfků kol automobilů

At the end of every automotive assembly line, there is a quality control process where factory workers check produced cars for potential defects. The computer vision field, especially neural networks for images, have great potential to complement human staff in order to produce as safe and reliable cars as possible. In this thesis we focus on the validation, whether all four wheels on a single car match in size and type. We introduce and experiment with both neural networks and traditional computer vision techniques. The approach we use is to first detect the car then classify its wheels and try to estimate their size. In the end we build a functional prototype of the system that is running in real-time. The data for this thesis were recorded in Škoda Auto factory in Mladá Boleslav in cooperation with the company. 1Každá automobilová linka končí kontrolou kvality při které pracovníci kontrolují auta kvůli případným defektům. Obor strojového vidění, zejména neuronové sítě pro zpraco- vání obrazu, má velký potenciál doplňovat schopnosti personálu, aby bylo možné vyrábět co nejbezpečnější a nejspolehlivější automobily. V této práci se zaměřujeme na kontrolu toho, zda se všechna čtyři kola na jednom automobilu shodují velikostí a typem. Ex- perimentujeme jak s neuronovými sítěmi, tak i s více tradičními technikami strojového vidění. Zvolený přístup spočívá v tom nejdříve detekovat auto a kola, a následně kola klasifikovat a pokusit se stanovit jejich velikost. Na konci práce představujeme funkční prototyp systému, který běží v reálném čase. Data pro tuto práci byla pořízena v továrně Škoda Auto v Mladé Boleslavi ve spolupráci s touto společností. 1Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic

Aeronautical Engineering: A continuing bibliography with indexes

This bibliography lists 529 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in May 1980

Aeronautical engineering: A continuing bibliography with indexes (supplement 272)

This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

2024 Student Symposium Program and Book of Abstracts

The mission of the UMaine Student Symposium is to give graduate and undergraduate students from UMaine and UMaine Machias the opportunity to showcase their work, research, and creative activities to the greater community, fostering conversations and collaborations that will benefit the future of Maine and beyond