114 research outputs found

    Recent developments in fibre optic shape sensing

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    This paper presents a comprehensive critical review of technologies used in the development of fibre optic shape sensors (FOSSs). Their operation is based on multi-dimensional bend measurements using a series of fibre optic sensors. Optical fibre sensors have experienced tremendous growth from simple bend sensors in 1980s to full three-dimensional FOSSs using multicore fibres in recent years. Following a short review of conventional contact-based shape sensor technologies, the evolution trend and sensing principles of FOSSs are presented. This paper identifies the major optical fibre technologies used for shape sensing and provides an account of the challenges and emerging applications of FOSSs in various industries such as medical robotics, industrial robotics, aerospace and mining industry

    Development of a fiber-based shape sensor for navigating flexible medical tools

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    Robot-assisted minimally invasive surgical procedure (RAMIS) is a subfield of minimally invasive surgeries with enhanced manual dexterity, manipulability, and intraoperative image guidance. In typical robotic surgeries, it is common to use rigid instruments with functional articulating tips. However, in some operations where no adequate and direct access to target anatomies is available, continuum robots can be more practical, as they provide curvilinear and flexible access. However, their inherent deformable design makes it difficult to accurately estimate their 3D shape during the operation in real-time. Despite extensive model-based research that relies on kinematics and mechanics, accurate shape sensing of continuum robots remains challenging. The state-of-the-art tracking technologies, including optical trackers, EM tracking systems, and intraoperative imaging modalities, are also unsuitable for this task, as they all have shortcomings. Optical fiber shape sensing solutions offer various advantages compared to other tracking modalities and can provide high-resolution shape measurements in real-time. However, commercially available fiber shape sensors are expensive and have limited accuracy. In this thesis, we propose two cost-effective fiber shape sensing solutions based on multiple single-mode fibers with FBG (fiber Bragg grating) arrays and eccentric FBGs. First, we present the fabrication and calibration process of two shape sensing prototypes based on multiple single-mode fibers with semi-rigid and super-elastic substrates. Then, we investigate the sensing mechanism of edge-FBGs, which are eccentric Bragg gratings inscribed off-axis in the fiber's core. Finally, we present a deep learning algorithm to model edge-FBG sensors that can directly predict the sensor's shape from its signal and does not require any calibration or shape reconstruction steps. In general, depending on the target application, each of the presented fiber shape sensing solutions can be used as a suitable tracking device. The developed fiber sensor with the semi-rigid substrate has a working channel in the middle and can accurately measure small deflections with an average tip error of 2.7 mm. The super-elastic sensor is suitable for measuring medium to large deflections, where a centimeter range tip error is still acceptable. The tip error in such super-elastic sensors is higher compared to semi-rigid sensors (9.9-16.2 mm in medium and large deflections, respectively), as there is a trade-off between accuracy and flexibility in substrate-based fiber sensors. Edge-FBG sensor, as the best performing sensing mechanism among the investigated fiber shape sensors, can achieve a tip accuracy of around 2 mm in complex shapes, where the fiber is heavily deflected. The developed edge-FBG shape sensing solution can compete with the state-of-the-art distributed fiber shape sensors that cost 30 times more

    FBG-Based Triaxial Force Sensor Integrated with an Eccentrically Configured Imaging Probe for Endoluminal Optical Biopsy

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    Accurate force sensing is important for endoluminal intervention in terms of both safety and lesion targeting. This paper develops an FBG-based force sensor for robotic bronchoscopy by configuring three FBG sensors at the lateral side of a conical substrate. It allows a large and eccentric inner lumen for the interventional instrument, enabling a flexible imaging probe inside to perform optical biopsy. The force sensor is embodied with a laser-profiled continuum robot and thermo drift is fully compensated by three temperature sensors integrated on the circumference surface of the sensor substrate. Different decoupling approaches are investigated, and nonlinear decoupling is adopted based on the cross-validation SVM and a Gaussian kernel function, achieving an accuracy of 10.58 mN, 14.57 mN and 26.32 mN along X, Y and Z axis, respectively. The tissue test is also investigated to further demonstrate the feasibility of the developed triaxial force senso

    Soft manipulators and grippers: A review

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    Soft robotics is a growing area of research which utilizes the compliance and adaptability of soft structures to develop highly adaptive robotics for soft interactions. One area in which soft robotics has the ability to make significant impact is in the development of soft grippers and manipulators. With an increased requirement for automation, robotics systems are required to perform task in unstructured and not well defined environments; conditions which conventional rigid robotics are not best suited. This requires a paradigm shift in the methods and materials used to develop robots such that they can adapt to and work safely in human environments. One solution to this is soft robotics, which enables soft interactions with the surroundings while maintaining the ability to apply significant force. This review paper assesses the current materials and methods, actuation methods and sensors which are used in the development of soft manipulators. The achievements and shortcomings of recent technology in these key areas are evaluated, and this paper concludes with a discussion on the potential impacts of soft manipulators on industry and society

    Control-based 4D printing: adaptive 4D-printed systems

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    Building on the recent progress of four-dimensional (4D) printing to produce dynamic structures, this study aimed to bring this technology to the next level by introducing control-based 4D printing to develop adaptive 4D-printed systems with highly versatile multi-disciplinary applications, including medicine, in the form of assisted soft robots, smart textiles as wearable electronics and other industries such as agriculture and microfluidics. This study introduced and analysed adaptive 4D-printed systems with an advanced manufacturing approach for developing stimuli-responsive constructs that organically adapted to environmental dynamic situations and uncertainties as nature does. The adaptive 4D-printed systems incorporated synergic integration of three-dimensional (3D)-printed sensors into 4D-printing and control units, which could be assembled and programmed to transform their shapes based on the assigned tasks and environmental stimuli. This paper demonstrates the adaptivity of these systems via a combination of proprioceptive sensory feedback, modeling and controllers, as well as the challenges and future opportunities they present

    Optical Multicore Fiber Shape Sensors. A numerical and experimental performance assessment

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    [EN] Structural Health Monitoring (SHM) is a discipline that quantitatively assesses the integrity and performance of infrastructures, relying on sensors, and support the development of efficient Maintenance and Rehabilitation (M&R) plans. Optical Multicore Fiber (MCF) Shape Sensors offer an innovative alternative to traditional methods and enable the reconstruction of the deformed shape of structures directly and in real-time, with no need of computation models or visual contact and exploiting all the advantages of Optical Fiber Sensors (OFS) technology. Despite the intense research efforts centered on this topic by research groups worldwide, a comprehensive investigation on the parameters that influence the performance of these sensors has not been conducted yet. The first part of the thesis presents a numerical study that examines the effects of strain measurement accuracy and core position errors on the performance of optical multicore fiber shape sensors in sensing three-dimensional curvature, which is at the basis of shape reconstruction. The analysis reproduces the strain measurement process using Monte Carlo Method (MCM) and identifies several parameters which play a key role in the phenomenon, including core spacing (distance between outer cores and sensor axis), number of cores and curvature measured. Finally, a set of predictive models were calibrated, by fitting the results of the simulations, to predict the sensors performance. Afterward, an experimental study is proposed to evaluate the performance of optical multicore fiber in sensing shape, with particular focus on the influence of strain sensors length. Two shape sensors were fabricated, by inscribing long (8.0 mm) and short (1.5 mm) Fiber Bragg Gratings (FBG) into the cores of a multicore seven-core fiber. Thus, the performance of the two sensors was assessed and compared, at all the necessary phases for shape reconstruction: strain sensing, curvature calculation and shape reconstruction. To conclude, an innovative approach, based on the Saint-Venant's Torsion Theory, is presented to determine the twisting of multicore fiber and to compensate the errors due to twisting during shape reconstruction. The efficiency of the theoretical approach was then corroborated performing a series of twisting tests on a shape sensor, fabricated by inscribing FBGs sensors into an optical spun multicore seven-core fiber. The investigation of the mechanical behavior of multicore optical shape sensors has synergically involved diverse disciplines: Solid Mechanics, Photonics, Statistics and Data Analysis. Such multidisciplinary research has arisen from the prolific cooperation between the Institutes of the Institute of Science and Technology of Concrete (ICITECH) and the Institute of Telecommunications and Multimedia Applications (iTEAM) - Photonics Research Labs (PRL) - of Universitat Politècnica de València (UPV), in addition to valuable collaboration with other members of the European ITN-FINESSE project, to which this work belongs. This research work aims to enhance the performance optical multicore fiber shape sensors and support the development of new sensor geometries, with great potential for structural health monitoring applications.[ES] La Monitorización de la Salud Estructural (MSE) evalúa cuantitativamente la integridad y el comportamiento de las infraestructuras y permite desarrollar planes eficaces de Mantenimiento y Rehabilitación (M&R), utilizando los datos de los sensores. Sensores de forma basados en fibra óptica multinúcleo ofrecen una alternativa a los métodos tradicionales y permiten la reconstrucción de la deformada de estructuras de forma directa y en tiempo real, sin necesidad de modelos de cálculo o contacto visual y con todas las ventajas de la tecnología de los Sensores de Fibra Óptica (SFO). A pesar de los grandes esfuerzos en la investigación centrada en este tema por parte de los grupos de investigación de todo el mundo, todavía no se ha realizado una investigación exhaustiva que estudie los parámetros que influyen en el comportamiento de estos sensores. En la primera parte de la tesis se presenta un estudio numérico en el que se examinan los efectos de la precisión de la medición de la tensión y los errores de posición del núcleo en el comportamiento de los sensores de forma basados en fibra óptica multinúcleo para definir la curvatura tridimensional, que es la base de la reconstrucción de la forma. El análisis reproduce el proceso de medición de la tensión utilizando el método de Monte Carlo (MC) e identifica una serie de parámetros que desempeñan un papel en el proceso, entre ellos la separación del núcleo (distancia entre los núcleos exteriores y el eje del sensor), el número de núcleos y la curvatura medida. Por último, se calibró un conjunto de modelos de predicción ajustando los resultados de las simulaciones para predecir el comportamiento de los sensores. A continuación, se propone un estudio experimental para evaluar el comportamiento de los sensores de forma basado en fibra óptica multinúcleo, con especial atención en la influencia de la longitud de los sensores de deformación. Se fabricaron dos sensores de forma, inscribiendo Fiber Bragg Gratings (FBG) con longitudes de 8,0 mm y 1,5 mm en los núcleos de una fibra multinúcleo de siete núcleos. Así, se evaluó y comparó el comportamiento de los dos sensores en todas las fases necesarias para la reconstrucción de la forma, incluyendo la medición de la tensión, el cálculo de la curvatura y la reconstrucción de la forma. Para concluir, se presenta un enfoque innovador, basado en la Teoría de la Torsión de Saint-Venant, para determinar la torsión de la fibra multinúcleo y compensar los errores debidos a la torsión durante la reconstrucción de la forma. La eficiencia del enfoque teórico fue verificada realizando una serie de pruebas de torsión en un sensor de forma, fabricado inscribiendo los sensores de FBGs en una fibra óptica multinúcleo torcida y siete núcleos. La investigación del comportamiento mecánico de los sensores ópticos de forma multinúcleo ha involucrado sinérgicamente diversas disciplinas: Mecánica del sólido, Fotónica, Estadística y Análisis de datos. Esta investigación multidisciplinaria ha surgido de la prolífica cooperación entre el Instituto de Ciencia y Tecnología del Hormigón (ICITECH) y el Instituto de Telecomunicaciones y Aplicaciones Multimedia (iTEAM) - Laboratorio de Investigación Fotónica (LIF) - de la Universidad Politécnica de Valencia (UPV), además de la valiosa colaboración con otros miembros del proyecto europeo ITN-FINESSE, al que pertenece este trabajo. Este trabajo de investigación puede permitir mejorar el comportamiento de los sensores de forma basados en fibra óptica multinúcleo y apoyar el desarrollo de nuevas geometrías de sensores, con un gran potencial para aplicaciones de control de la salud estructural.[CA] Structural Health Monitoring (SHM) avalua quantitativament la integritat i el comportament de les infraestructures i permet desenrotllar plans eficaços de Maintenance and Rehabilitation (M&R), utilitzant les dades dels sensors. Optical Multicore Fiber (MCF) Shape Sensors oferixen una alternativa als mètodes tradicionals i permeten la reconstrucció de la forma de la deformació de les estructures de forma directa i en temps real, sense necessitat de models de càlcul o contacte visual i amb tots els avantatges de l'Optical Fiber Sensors (OFS) Technology. A pesar dels grans esforços en la investigació centrada en aquest tema per part dels grups d'investigació de tot el món, encara no s'ha realitzat una investigació exhaustiva que estudie els paràmetres que influïxen en el comportament d'aquestos sensors. En la primera part de la tesi es presenta un estudi numèric en què s'examinen els efectes de la precisió del mesurament de la tensió i els errors de posició del nucli en el comportament dels sensors de forma basats en fibra òptica multinucli per a definir la curvatura tridimensional, que és la base de la reconstrucció de la forma. L'anàlisi reproduïx el procés de mesurament de la tensió utilitzant el mètode de Monte Carlo (MC) i identifica una sèrie de paràmetres que exercixen un paper en el procés, entre ells la separació del nucli (distància entre els nuclis exteriors i l'eix del sensor), el nombre de nuclis i la mesura de la curvatura. Finalment, es va calibrar un conjunt de models de predicció ajustant els resultats de les simulacions per a predir el comportament dels sensors. A continuació, es proposa un estudi experimental per a avaluar el comportament dels sensors de forma basat en fibra òptica multinucli, amb especial atenció en la influència de la longitud dels sensors de deformació. Es van fabricar dos sensors de forma, inscrivint Fiber Bragg Gratings (FBG) amb longituds de 8,0 mm i 1,5 mm en els nuclis d'una fibra multinucli de set nuclis. Així, es va avaluar i es va comparar el comportament dels dos sensors en totes les fases necessàries per a la reconstrucció de la forma, incloent el mesurament de la tensió, el càlcul de la curvatura i la reconstrucció de la forma. Per a concloure, es presenta un enfocament innovador, basat en la Teoria de la Torsió de Saint-Venant, per a determinar la torsió de la fibra multinucli i compensar els errors deguts a la torsió durant la reconstrucció de la forma. L'eficiència de l'enfocament teòric va ser verificada realitzant una sèrie de proves de torsió en un sensor de forma, fabricat inscrivint els sensors de FBGs en una fibra òptica de set nuclis de filat múltiple. La investigació del comportament mecànic dels sensors òptics de forma multinucli ha involucrat sinèrgicament diverses disciplines: Mecànica del sòlid, Fotónica, Estadística i Anàlisi de dades. Aquesta investigació multidisciplinària ha sorgit de la prolífica cooperació entre l'Institut de Ciència i Tecnologia del Formigó (ICITECH) i l'Institut de Telecomunicacions i Aplicacions Multimèdia (iTEAM) - Laboratori de investigación fotònica (LIF) - de la Universitat Politècnica de València (UPV), a més de la valuosa col·laboració amb altres membres del projecte europeu ITN- FINESSE, al qual pertany aquest treball. Aquest treball d'investigació pot permetre millorar el comportament dels sensors de forma basats en fibra òptica multinucli i ajudar al desenrotllament de noves geometries de sensors, amb un gran potencial per a aplicacions de control de la salut estructural.Floris, I. (2020). Optical Multicore Fiber Shape Sensors. A numerical and experimental performance assessment [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/148715TESI

    Selecting an Appropriate Curvature Sensor for Fluidic Soft Robot and Modeling Sensor Reading vs Pressure vs Position

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    This research focuses on the study of a curvature sensor for a fluidic soft robot. Soft robot is a complete new dimension to traditional rigid robot. A soft robot is made up of materials like Silicon, PDMS and elastomeric polymers. The actuation method can be hydraulic, pneumatic or electric. Depending on its construction, it undergoes elongation, bending, twisting, or all of the three on actuation. It brings with it some important features like compliance with the object of interaction and robustness, which is an inspiration acquired from animals and plants. This results into useful applications in fields of rehabilitation, gripping delicate objects in food industries and allowing safe interaction for humans. The soft robot has large DOF, which allows it to maneuver in a way, which is difficult for the traditional robot. However, this large DOF makes the modeling of the soft robot for determining the robot state difficult and challenging. Another approach towards determining the robot state is using sensors. In this thesis, a thorough study is done to find out an appropriate curvature sensor to be embedded into the soft robot. The data from curvature sensor, pressure sensor and the vision system are collected in experiments undertaken with obstacles in the soft robot path. The collected data is used via machine learning technique to obtain trained model that determines the robot state and obstacle location

    Challenges of continuum robots in clinical context: a review

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    With the maturity of surgical robotic systems based on traditional rigid-link principles, the rate of progress slowed as limits of size and controllable degrees of freedom were reached. Continuum robots came with the potential to deliver a step change in the next generation of medical devices, by providing better access, safer interactions and making new procedures possible. Over the last few years, several continuum robotic systems have been launched commercially and have been increasingly adopted in hospitals. Despite the clear progress achieved, continuum robots still suffer from design complexity hindering their dexterity and scalability. Recent advances in actuation methods have looked to address this issue, offering alternatives to commonly employed approaches. Additionally, continuum structures introduce significant complexity in modelling, sensing, control and fabrication; topics which are of particular focus in the robotics community. It is, therefore, the aim of the presented work to highlight the pertinent areas of active research and to discuss the challenges to be addressed before the potential of continuum robots as medical devices may be fully realised
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