Conformal Robotic Stereolithography

Additive manufacturing by layerwise photopolymerization, commonly called stereolithography (SLA), is attractive due to its high resolution and diversity of materials chemistry. However, traditional SLA methods are restricted to planar substrates and planar layers that are perpendicular to a single-axis build direction. Here, we present a robotic system that is capable of maskless layerwise photopolymerization on curved surfaces, enabling production of large-area conformal patterns and the construction of conformal freeform objects. The system comprises an industrial six-axis robot and a custom-built maskless projector end effector. Use of the system involves creating a mesh representation of the freeform substrate, generation of a triangulated toolpath with curved layers that represents the target object to be printed, precision mounting of the substrate in the robot workspace, and robotic photopatterning of the target object by coordinated motion of the robot and substrate. We demonstrate printing of conformal photopatterns on spheres of various sizes, and construction of miniature three-dimensional objects on spheres without requiring support features. Improvement of the motion accuracy and development of freeform toolpaths would enable construction of polymer objects that surpass the size and support structure constraints imparted by traditional SLA systems.American Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipNational Institute of Mental Health (U.S.) (University of Michigan Microfluidics in Biomedical Sciences Training Program. 5T32-EB005582)Singapore-MIT Alliance for Research and Technology (SMART

A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

Modeling, optimizing and simulating robot calibration with accuracy improvement

This work describes techniques for modeling, optimizing and simulating calibration processes ofrobots using off-line programming. The identification of geometric parameters of the nominalkinematic model is optimized using techniques of numerical optimization of the mathematicalmodel. The simulation of the actual robot and the measurement system is achieved by introducingrandom errors representing their physical behavior and its statistical repeatability. An evaluationof the corrected nominal kinematic model brings about a clear perception of the influence ofdistinct variables involved in the process for a suitable planning, and indicates a considerableaccuracy improvement when the optimized model is compared to the non-optimized one

Design and Validation of a Portable Wireless Data Acquisition System for Measuring Human Joint Angles in Medical Applications

A prototype sensor system to capture and measure human joint movements in medical applications was developed. An algorithm that uses measurements from two IMU sensors to estimate the angle of one human joint was developed. Custom-made hardware and software were developed. Validation results showed 0.67° maximum error in static condition, 1.56° maximum RMSE for dynamic measurements and 2.5° average error during fast movements’ tests. The prototype has been successfully used by medical teams

An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

This paper presents an overview of the literature on kinematic and calibration models of parallel mechanisms, the influence of sensors in the mechanism accuracy and parallel mechanisms used as sensors. The most relevant classifications to obtain and solve kinematic models and to identify geometric and non-geometric parameters in the calibration of parallel robots are discussed, examining the advantages and disadvantages of each method, presenting new trends and identifying unsolved problems. This overview tries to answer and show the solutions developed by the most up-to-date research to some of the most frequent questions that appear in the modelling of a parallel mechanism, such as how to measure, the number of sensors and necessary configurations, the type and influence of errors or the number of necessary parameters

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

IMUs: validation, gait analysis and system’s implementation

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Falls are a prevalent problem in actual society. The number of falls has been increasing greatly in the last fifteen years. Some falls result in injuries and the cost associated with their treatment is high. However, this is a complex problem that requires several steps in order to be tackled. Namely, it is crucial to develop strategies that recognize the mode of locomotion, indicating the state of the subject in various situations, namely normal gait, step before fall (pre-fall) and fall situation. Thus, this thesis aims to develop a strategy capable of identifying these situations based on a wearable system that collects information and analyses the human gait. The strategy consists, essentially, in the construction and use of Associative Skill Memories (ASMs) as tools for recognizing the locomotion modes. Consequently, at an early stage, the capabilities of the ASMs for the different modes of locomotion were studied. Then, a classifier was developed based on a set of ASMs. Posteriorly, a neural network classifier based on deep learning was used to classify, in a similar way, the same modes of locomotion. Deep learning is a technique actually widely used in data classification. These classifiers were implemented and compared, providing for a tool with a good accuracy in recognizing the modes of locomotion. In order to implement this strategy, it was previously necessary to carry out extremely important support work. An inertial measurement units’ (IMUs) system was chosen due to its extreme potential to monitor outpatient activities in the home environment. This system, which combines inertial and magnetic sensors and is able to perform the monitoring of gait parameters in real time, was validated and calibrated. Posteriorly, this system was used to collect data from healthy subjects that mimicked Fs. Results have shown that the accuracy of the classifiers was quite acceptable, and the neural networks based classifier presented the best results with 92.71% of accuracy. As future work, it is proposed to apply these strategies in real time in order to avoid the occurrence of falls.As quedas são um problema predominante na sociedade atual. O número de quedas tem aumentado bastante nos últimos quinze anos. Algumas quedas resultam em lesões e o custo associado ao seu tratamento é alto. No entanto, trata-se de um problema complexo que requer várias etapas a serem abordadas. Ou seja, é crucial desenvolver estratégias que reconheçam o modo de locomoção, indicando o estado do sujeito em várias situações, nomeadamente, marcha normal, passo antes da queda (pré-queda) e situação de queda. Assim, esta tese tem como objetivo desenvolver uma estratégia capaz de identificar essas situações com base num sistema wearable que colete informações e analise a marcha humana. A estratégia consiste, essencialmente, na construção e utilização de Associative Skill Memories (ASMs) como ferramenta para reconhecimento dos modos de locomoção. Consequentemente, numa fase inicial, foram estudadas as capacidades das ASMs para os diferentes modos de locomoção. Depois, foi desenvolvido um classificador baseado em ASMs. Posteriormente, um classificador de redes neuronais baseado em deep learning foi utilizado para classificar, de forma semelhante, os mesmos modos de locomoção. Deep learning é uma técnica bastante utilizada em classificação de dados. Estes classificadores foram implementados e comparados, fornecendo a uma ferramenta com uma boa precisão no reconhecimento dos modos de locomoção. Para implementar esta estratégia, era necessário realizar previamente um trabalho de suporte extremamente importante. Um sistema de unidades de medição inercial (IMUs), foi escolhido devido ao seu potencial extremo para monitorizar as atividades ambulatórias no ambiente domiciliar. Este sistema que combina sensores inerciais e magnéticos e é capaz de efetuar a monitorização de parâmetros da marcha em tempo real, foi validado e calibrado. Posteriormente, este Sistema foi usado para adquirir dados da marcha de indivíduos saudáveis que imitiram quedas. Os resultados mostraram que a precisão dos classificadores foi bastante aceitável e o classificador baseado em redes neuronais apresentou os melhores resultados com 92.71% de precisão. Como trabalho futuro, propõe-se a aplicação destas estratégias em tempo real de forma a evitar a ocorrência de quedas

Force sensing enhancement of robot system

At present there is a general industrial need to improve robot performance. Force feedback, which involves sensing and actuation, is one means of improving the relative position between the workpiece and the end-effector. In this research work various causes of errors and poor robot performance are identified. Several methods of improving the performance of robotic systems are discussed. As a result of this research, a system was developed which is interposed between the wrist and the gripper of the manipulator. This system integrates a force sensor with a micro-manipulator, via an electronic control unit, with a micro-computer to enhance a robot system. The force sensor, the micromanipulator and the electronic control unit, were all designed and manufactured at the robotic centre of Middlesex Polytechnic. The force feedback is provided by means of strain gauges and the associated bridge circuitry. Control algorithms which define the relationship between the force detected and the motion required are implemented in the software. The software is capable of performing two specific tasks in real time, these are: 1- Inserting a peg into a hole 2- Following an unknown geometric path A rig was designed and manufactured to enable the robot to follow different geometric shapes and paths in which force control was achieved mainly by control of the micro-manipulator

Desarrollo y verificación de procedimientos de modelado cinemático y técnicas de calibración de laser trackers basadas en medición de red de reflectores

Los métodos de calibración existentes se basan en un modelo de errores geométricos y precisan del uso de patrones metrológicos de alto rango, así como de la realización de un gran número de mediciones, todo ello en un entorno en condiciones controladas. Esto supone una gran inversión en medios, tiempo y personal cualificado. La presente tesis tiene por objetivo el desarrollo y validación de un procedimiento de calibración de Laser Trackers rápido, sencillo y preciso basado en el modelo cinemático y al alcance de cualquier usuario sin conocimientos metrológicos avanzados.Para ello se realiza un modelado cinemático del laser tracker (LT) siguiendo el modelo de Denavit-Hartenberg. Este modelo se completa con matrices de error asociadas a cada sistema de referencia del modelo cinemático que, siguiendo la formulación de Slocum en su libro sobre diseño de máquinas de precisión, consigue corregir el modelo cinemático introduciendo un conjunto de parámetros de error. En la formulación tradicional, estos parámetros de error tienen valores constantes para cada articulación de la cadena cinemática, pero en esta tesis se ha realizado una formulación variable en función de la posición de cada articulación, lo cual contribuye a mejorar en gran manera el comportamiento del procedimiento de calibración.El modelo de calibración planteado se ha verificado primeramente por medio de datos sintéticos con los cuales se han simulado las mediciones de diversas mallas de reflectores realizadas por un LT afectado por un vector de parámetros conocidos. Posteriormente se ha utilizado el modelo de calibración para la identificación de los parámetros de error y la corrección de las mediciones.Una vez verificado el modelo con datos sintéticos, se ha procedido a verificarlo con datos reales. Para ello se ha colocado una malla de reflectores en la mesa de una máquina de medición por coordenadas (MMC). La malla de reflectores se ha medido con la MMC y con un LT desde 5 posiciones distintas. La aplicación del modelo de calibración muestra la mejora obtenida en la precisión de medición del LT. Estas mediciones se han utilizado también para definir y comparar distintas estrategias de calibración en ausencia de los valores nominales de medidas proporcionadas por la MMC. Igualmente se han utilizado para comparar los resultados obtenidos por la calibración cinemática con los de la calibración convencional basada en errores geométricos. Se comprueba que la calibración cinemática es más fácilmente extrapolable a todo el ámbito de medición del LT que la calibración geométrica. El criterio de calibración empleado se basa en el hecho de que la distancia entre cada pareja de reflectores debe ser la misma independientemente de la posición del LT desde la que hayan sido medidas.Con el modelo verificado, se ha planteado un ensayo de calibración en condiciones reales. En base a un ensayo de sensibilidad, en el que se ha estudiado la influencia de cada parámetro de error en el error global de medición del LT se han determinado las posiciones óptimas de los reflectores a utilizar en el ensayo de calibración. Esta información, junto con la obtenida del estudio de las estrategias de calibración ha permitido establecer las condiciones idóneas para el ensayo de calibración. Se han colocado 27 reflectores en las posiciones preestablecidas, midiéndose desde 5 posiciones del LT. El resultado de la calibración se ha evaluado con dos criterios distintos. Primero con el novedoso criterio introducido en la tesis de consistencia de distancias entre reflectores y el método tradicional de error de posicionamiento de reflectores, el cual supone la necesidad de transformar todas las medidas a un mismo sistema de referencia para poder compararlas.Dado que no se dispone de valores nominales con los que verificar los resultados de la calibración, se han aplicado los parámetros de calibración a las mediciones realizadas en la MMC, verificándose un incremento en la precisión de medición del LT similar a la esperada.Los reflectores han sido medidos desde posiciones distintas del LT, esto hace que el ángulo de incidencia del haz del láser en el reflector no sea siempre el óptimo. Por ello se ha estudiado la influencia, en el error de medición del LT, del ángulo de incidencia del haz del láser en el reflector.La conclusión de la tesis es que se ha obtenido el método de calibración que se esperaba, el cual con una reducida cantidad de mediciones en condiciones ambientales, permite mejorar la precisión del LT. El método consigue mejoras por encima de la calibración del fabricante del LT y además está al alcance de cualquier usuario sin conocimientos metrológicos avanzados.<br /