Direct Visual Servoing Framework based on Optimal Control for Redundant Joint Structures

This paper presents a new framework based on optimal control to define new dynamic visual controllers to carry out the guidance of any serial link structure. The proposed general method employs optimal control to obtain the desired behaviour in the joint space based on an indicated cost function which determines how the control effort is distributed over the joints. The proposed approach allows the development of new direct visual controllers for any mechanical joint system with redundancy. Finally, authors show experimental results and verifications on a real robotic system for some derived controllers obtained from the control framework.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

Traitement du cancer pulmonaire non à petites cellules par radiothérapie stéréotaxique d’ablation

Les néoplasies pulmonaires demeurent la première cause de décès par cancer au Québec représentant près de 6000 décès par année. Au cours des dernières années, la radiothérapie stéréotaxique d’ablation (SABR) s’est imposée comme un traitement alternatif à la résection anatomique pour les patients inopérables atteints d’un cancer pulmonaire non à petites cellules de stade précoce. Il s’agit d’une modalité de traitement qui permet d’administrer des doses élevées, typiquement 30-60 Gy en 1-8 fractions, dans le but de cibler précisément le volume de traitement tout en épargnant les tissus sains. Le Centre Hospitalier de l’Université de Montréal s’est muni en 2009 d’un appareil de SABR de fine pointe, le CyberKnife™ (CK), un accélérateur linéaire produisant un faisceau de photons de 6 MV dirigé par un bras robotisé, permettant d’administrer des traitements non-coplanaires avec une précision infra-millimétrique. Ce mémoire est dédié à la caractérisation de certains enjeux cliniques et physiques associés au traitement par CK. Il s’articule autour de deux articles scientifiques revus par les pairs. D’une part, une étude prospective clinique présentant les avantages de la SABR pulmonaire, une technique qui offre un excellent contrôle tumoral à long terme et aide au maintien de la qualité de vie et de la fonction pulmonaire. D’autre part, une étude de physique médicale illustrant les limites de l’acquisition d’images tomodensitométriques en auto-rétention respiratoire lors de la planification de traitement par CK.

Effects of Economic Factors on Adoption of Robotics and Consequences of Automation for Productivity Growth of Dairy Farms. Factor Markets Working Paper No. 32, December 2012

In the long term, productivity and especially productivity growth are necessary conditions for the survival of a farm. This paper focuses on the technology choice of a dairy farm, i.e. the choice between a conventional and an automatic milking system. Its aim is to reveal the extent to which economic rationality explains investing in new technology. The adoption of robotics is further linked to farm productivity to show how capital-intensive technology has affected the overall productivity of milk production. The empirical analysis applies a probit model and an extended Cobb-Douglas-type production function to a Finnish farm-level dataset for the years 2000–10. The results show that very few economic factors on a dairy farm or in its economic environment can be identified to affect the switch to automatic milking. Existing machinery capital and investment allowances are among the significant factors. The results also indicate that the probability of investing in robotics responds elastically to a change in investment aids: an increase of 1% in aid would generate an increase of 2% in the probability of investing. Despite the presence of non-economic incentives, the switch to robotic milking is proven to promote productivity development on dairy farms. No productivity growth is observed on farms that keep conventional milking systems, whereas farms with robotic milking have a growth rate of 8.1% per year. The mean rate for farms that switch to robotic milking is 7.0% per year. The results show great progress in productivity growth, with the average of the sector at around 2% per year during the past two decades. In conclusion, investments in new technology as well as investment aids to boost investments are needed in low-productivity areas where investments in new technology still have great potential to increase productivity, and thus profitability and competitiveness, in the long run.

ROVIM T2D: Um robô autónomo de vigilância de instalações militares

Os avanços técnológicos da última década permitiram um crescimento nas aplicações militares de veículos autónomos. Com o objetivo de explorar o seu potêncial na vigilância de instalações militares, a Academia Militar encomendou o desenvolvimento e construção de um protótipo funcional de um veículo autónomo. Nesta dissertação os sistemas de tração, travagem e direção desse protótipo são abordados. A literatura atual foca-se em aplicações comerciais de veículos rodoviários, onde a autonomia é o principal problema. No entanto, equipas não profissionais lidam antes disso com dificuldades em capturar uma visão clara do projecto e fracos procedimentos de segurança. Uma moto-quatro com um módulo de baterias elétricas e atuadores embarcados para os sistemas da tração, travagem e direção, assim como os mecanismos de controlo e interface, é aqui proposta e avaliada, numa abordagem focada na flexibilidade de desenho e na segurança dos utilizadores. As limitações da solução proposta são identificadas e são propostas correções.

Simulating Nursing: Rhetoric, Materiality, and Disciplinary Learning

Thesis (Ph.D.)--University of Washington, 2016-06

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

Dispositivo Médico-Cirúrgico Eletromecânico para Laparoscopia

Os avanços realizados nas técnicas cirúrgicas têm permitido que o tempo de recuperação outrora contado em dias ou até semanas tenha sido reduzido para horas, com os pacientes a saírem do hospital pelo seu próprio pé pouco tempo após a intervenção. Tal resulta numa redução do tempo de recuperação, menos desconforto para o paciente e consequente redução dos custos associados ao internamento. A redução nos tempos de recuperação é fundamentalmente devida às técnicas cirúrgicas minimamente invasivas que assentam sobretudo na utilização de instrumentos laparoscópicos. A anestesia é agora muitas vezes local ou apenas uma sedação, ficando o paciente sob efeito da anestesia durante um período menor quando comparado com as técnicas tradicionais. O desenvolvimento de dispositivos laparoscópicos que permitam ao cirurgião maior manobrabilidade associada a uma atuação simples, sem os movimentos invertidos inerentes aos instrumentos tradicionais, irão permitir realizar intervenções que outrora seriam realizadas com as técnicas tradicionais, de forma segura e menos intrusiva reduzindo o risco de complicações pós-operatórias. Os dispositivos laparoscópicos mais avançados associados a certas técnicas cirúrgicas, permitem a realização de intervenções complexas e de grande minucia através de apenas um orifício LESS (Laparoendoscopic single-site surgery), ou no caso de ser realizada com robô, R-LESS (Robotic laparoendoscopic single-site surgery); reduzindo de forma ainda mais acentuada o tempo de recuperação e o tamanho da cicatriz. O aumento da manobrabilidade dos dispositivos laparoscópicos é obtida através da inclusão de sistemas eletromecânicos relativamente complexos que tentam transpor o movimento da mão para a pinça dentro do paciente. No entanto, a adição destes sistemas podem tornar a manipulação desses dispositivos pouco intuitiva e pouco ergonómica, sobretudo se forem usados com apenas uma das mãos. Por outro lado, quando a atuação deixa de ser realizada de forma puramente mecânica e direta o cirurgião perde sensibilidade da força que está a ser exercida pelo dispositivo já que esta passa a ser efetuada através de um sistema assistido, como por exemplo motores elétricos, sistemas hidráulicos ou pneumáticos. Estes fatores resultam que a aceitação destes dispositivos pelos cirurgiões não tenha sido fácil. Para contornar este problema, o dispositivo desenvolvido para além de grande capacidade de manobra, oferece atuação natural e portabilidade. Contempla uma componente háptica de atuação hidráulica que ajudará o cirurgião a melhor perceci-onar o que se passa na ponta da pinça. Como o movimento da pinça é controlado por um sistema eletromecânico é possível escalonar a amplitude do movimento de entrada e reduzir o tremor fisiológico das mãos. A pinça e respetiva haste é convencional podendo ser usados os trocarts já existentes. Foi desenvolvido um protótipo virtual com todos os componentes necessários para um funcionamento integral. No então não foram realizados protótipos físicos de todos os componentes, nem se sabe como os diferentes módulos interagem entre si.

Novel hardwired distributive tactile sensing system for medical applications

This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and ‘touch’ information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.

Non-linear hierarchical visualisation

This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.

Realising competitive advantage:bicycle manufacture - manufacturing engineering and management

Students at Cranfield Manufacturing Systems Centre helped Brompton Bikes formulate a strategy to meet rapid sales growth. The students took up Operations Excellence MSc, a two-year part-time programme based on the Cranfield MSc in Engineering and Management of Manufacturing Systems, include the Realising Competitive Manufacture module, which is set out to consolidate and embed the knowledge and skills developed throughout the two-year programme. Guided by StratNav process, the students analysed the product families of Brompton, established the basis on which they compete in the market place, and then benchmarked against key competitors. The top five developments identified to be needed by Brompton are: the formation of group technology cells, creation of a robotic brazing facility, and training and recruitment initiatives for production staff.

Modular system design and control for flexible assembly

Flexible Assembly Systems (FASs) are normally associated with the automatic, or robotic, assembly of products, supported by automated material handling systems. However, manual assembly operations are still prevalent within many industries, where the complexity and variety of products prohibit the development of suitable automated assembly equipment. This article presents a generic model for incorporating flexibility into the design and control of assembly operations concerned with high variety/low volume manufacture, drawing on the principles for Flexible Manufacturing Systems (FMS) and Just-in-Time (JIT) delivery. It is based on work being undertaken in an electronics company where the assembly operations have been overhauled and restructured in response to a need for greater flexibility, shorter cycle times and reduced inventory levels. The principles employed are in themselves not original. However, the way they have been combined and tailored has created a total manufacturing control system which represents a new concept for responding to demands placed on market driven firms operating in an uncertain environment.

An optical fiber Bragg grating tactile sensor

Tactile sensors are needed for many emerging robotic and telepresence applications such as keyhole surgery and robot operation in unstructured environments. We have proposed and demonstrated a tactile sensor consisting of a fibre Bragg grating embedded in a polymer "finger". When the sensor is placed in contact with a surface and translated tangentially across it measurements on the changes in the reflectivity spectrum of the grating provide a measurement of the spatial distribution of forces perpendicular to the surface and thus, through the elasticity of the polymer material, to the surface roughness. Using a sensor fabricated from a Poly Siloxane polymer (Methyl Vinyl Silicone rubber) spherical cap 50 mm in diameter, 6 mm deep with an embedded 10 mm long Bragg grating we have characterised the first and second moment of the grating spectral response when scanned across triangular and semicircular periodic structures both with a modulation depth of 1 mm and a period of 2 mm. The results clearly distinguish the periodicity of the surface structure and the differences between the two different surface profiles. For the triangular structure a central wavelength modulation of 4 pm is observed and includes a fourth harmonic component, the spectral width is modulated by 25 pm. Although crude in comparison to human senses these results clearly shown the potential of such a sensor for tactile imaging and we expect that with further development in optimising both the grating and polymer "finger" properties a much increased sensitivity and spatial resolution is achievable.

Knowledge-based Robot Control

The paper is related with the problem of developing autonomous intelligent robots for complex environments. In details it outlines a knowledge-based robot control architecture that combines several techniques in order to supply an ability to adapt and act autonomously in complex environments. The described architecture has been implemented as a robotic system that demonstrates its operation in dynamic environment. Although the robotic system demonstrates a certain level of autonomy, the experiments show that there are situation, in which the developed base architecture should be complemented with additional modules. The last few chapters of the paper describe the experimentation results and the current state of further research towards the developed architecture.