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Greenspan, Michael A. "Robotic active tactile sensing skills." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/7557.
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This thesis examines the use of tactile sensing for robotic contact skills. Two skills were developed which successfully tracked the contact of a plane and a sphere in the presence of positional uncertainties and varying applied forces. In the plane tracking skill, the normal force of the contact as well as a rotational moment about an axis of the sensor was tracked. In the sphere tracking skill, the normal force and positional variations lateral to the sensor were tracked. This work is significant in that it represents the first attempt, to the author's knowledge, at implementing these skills using pure tactile sensing.
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Dudeney, William Leonard. "Novel displacement sensing : towards robotic tunnelling." Thesis, Loughborough University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392510.
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Jentoft, Leif Patrick. "Sensing and Control for Robust Grasping with Simple Hardware." Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11657.
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Robots can move, see, and navigate in the real world outside carefully structured factories, but they cannot yet grasp and manipulate objects without human intervention. Two key barriers are the complexity of current approaches, which require complicated hardware or precise perception to function effectively, and the challenge of understanding system performance in a tractable manner given the wide range of factors that impact successful grasping. This thesis presents sensors and simple control algorithms that relax the requirements on robot hardware, and a framework to understand the capabilities and limitations of grasping systems.Engineering and Applied Sciences
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Yuan, Wenzhen Ph D. Massachusetts Institute of Technology. "High-resolution tactile sensing for robotic perception." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120267.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 107-113).
Why is it so difficult for the present-day robots to act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. A recently developed high-resolution tactile sensor, GelSight, which measures detailed information about the geometry and traction field on the contact surface, shows substantial potential for extending the application of tactile sensing in robotics. The major questions are: (1) What physical information is available from the high-resolution sensor? (2) How can the robot interpret and use this information? This thesis aims at addressing the two questions above. On the one hand, the tactile feedback helps robots to interact better with the environment, i.e., perform better exploration and manipulation. I investigate various techniques for detecting incipient slip and full slip during contact with objects, which helps a robot to grasp them securely. On the other hand, tactile sensing also helps a robot to better understand the physical environment. That can be reflected in estimating the material properties of the surrounding objects. I will present my work on using tactile sensing to estimate the hardness of arbitrary objects, and making a robot autonomously explore the comprehensive properties of common clothing. I also show our work on the unsupervised exploration of latent properties of fabrics through cross-modal learning with vision and touch.
by Wenzhen Yuan.
Ph. D.
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Dubey, Venketeshwar Nath. "Sensing and control within a robotic end effector." Thesis, University of Southampton, 1997. https://eprints.soton.ac.uk/193195/.
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This research programme investigates aspects of end effector design and control, to carry out grasping operations in a range of unstructured environments. A conceptual three fingered end effector design has been developed. The articulated finger is operated by a novel mechanism which provides all the finger motions. Detailed force and kinematic analyses have been carried out which establish mechanical integrity of the system and help size the various finger components. A vectorial method of link representation has been used to derive finger kinematics. This representation has been used for position control in the controller. A numerical technique based on the Newton- Raphson method has been derived to undertake the finger's inverse kinematics in realtime. To validate the theoretical operation of the finger drive, a mechanism has been built with the necessary electronic interface, and programmed for position control. A photoelasticity based sensor has been developed which is capable of detecting applied force as well as slip and is largely immune to external disturbances. The sensor has a small size allowing it to be easily incorporated into a robotic finger. Mechanics of slip has been investigated to develop a theoretical model of the slip sensor. This allows modelling of various material and geometrical parameters involved in its design. In order to control the end effector, grasping strategies have been planned and a controller structure defined. The top level of the controller uses the kinematic relation to move the finger to a goal position. When fingers make contact with an object, the controller switches over to an inner fiizzy logic algorithm. The rule base of the fiizzy logic ensures that a stable grasp has been acquired with minimum fingertip force. The implementation of the fuzzy logic has been validated on an experimental test-rig. It has been found that the controller applies different minimum fingertip force to objects of different mass and it responds very quickly to the external disturbances by applying extra force to the object. The fingertip force comes back to its previous level as soon as the disturbance vanishes. The important feature exhibited by the controller is that it forms optimal grasp of objects without knowing their mass and frictional properties. This offers a very useful capability to an end effector controller operating in unstructured environments. A complete model of the end effector has been developed which ensures equilibrium and stability of the grasped object taking dynamic conditions of grasp into account. The model estimates unbalances in position, force and moment of the grasped object and tries to minimise these unbalances. The simulated results have shown that for every grasp situation, the algorithm is capable of minimising the unbalances and the operation of the algorithm is fast enough for real-time applications.
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Ospina, Triviño Andrés Felipe. "Intrinsic tactile sensing system for robotic dexterous manipulation." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066369/document.
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La détection tactile et la détection de glissement jouent un rôle important en permettant la manipulation robotique dextre des objets. Ainsi, le développement d'un système de capteur tactile entièrement intégré à haute résolution présente un intérêt certain. Ces travaux traitent de la conception et de la mise en place d'un système tactile intrinsèque basé sur un ensemble de capteurs MEMs de force à 3 axes et la détection du glissement avec ce système. Afin de créer un système tactile, les capteurs de force à 3 axes sont protégés par un revêtement, une étude sur le revêtement est réalisée. Deux systèmes intrinsèques différents basés sur un ensemble de capteurs de force à 3 axes sont développés, le premier est utilisé comme test de faisabilité de ce type de système. Le deuxième système intrinsèque est adapté à un doigt robotique à surface souple. Les systèmes proposés mesurent trois composants de force, le couple normal à la surface de contact et la position du centre de contact appliqué sur sa surface sensible. Les deux systèmes sont caractérisés et testés. La détection du glissement avec un système tactile intrinsèque est testée également. La détection du glissement est faite par l'application de la théorie de la surface limite et du modèle de contact viscoélastiqueTactile sensing and slip detection plays an important role in enabling robotic dexterous object manipulation. Thus developing a high-resolution fully integrated tactile sensor system is of great interest. This work deals the design and implementation of an intrinsic tactile sensing system based on a set of 3-axis force MEMs sensors and the detection of slippage with such system. In order to create a tactile system the 3-axis force sensors are protected by a coating, a study about the coating is made. Two different intrinsic systems based on an array of 3-axis force sensors are developed, the first one is used a feasibility test of this kind of system. The second intrinsic system is adapted to a robotic finger with soft surface. The proposed systems measures three-force components, the normal torque to the contact surface, and the position of the contact centroid applied to its sensitive surface. Both systems are characterized and tested. The detection of slippage with an intrinsic tactile system is tested. The application of the limit surface theory and the viscoelastic model of contact make the detection of slippage
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Corradi, Tadeo. "Integrating visual and tactile robotic perception." Thesis, University of Bath, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761005.
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The aim of this project is to enable robots to recognise objects and object categories by combining vision and touch. In this thesis, a novel inexpensive tactile sensor design is presented, together with a complete, probabilistic sensor-fusion model. The potential of the model is demonstrated in four areas: (i) Shape Recognition, here the sensor outperforms its most similar rival, (ii) Single-touch Object Recognition, where state-of-the-art results are produced, (iii) Visuo-tactile object recognition, demonstrating the benefits of multi-sensory object representations, and (iv) Object Classification, which has not been reported in the literature to date. Both the sensor design and the novel database were made available. Tactile data collection is performed by a robot. An extensive analysis of data encodings, data processing, and classification methods is presented. The conclusions reached are: (i) the inexpensive tactile sensor can be used for basic shape and object recognition, (ii) object recognition combining vision and touch in a probabilistic manner provides an improvement in accuracy over either modality alone, (iii) when both vision and touch perform poorly independently, the sensor-fusion model proposed provides faster learning, i.e. fewer training samples are required to achieve similar accuracy, and (iv) such a sensor-fusion model is more accurate than either modality alone when attempting to classify unseen objects, as well as when attempting to recognise individual objects from amongst similar other objects of the same class. (v) The preliminary potential is identified for real-life applications: underwater object classification. (vi) The sensor fusion model providesimprovements in classification even for award-winning deep-learning basedcomputer vision models.
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Ward-Cherrier, Benjamin Paul Jerome. "A biomimetic approach to tactile sensing and robotic manipulation." Thesis, University of Bristol, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761236.
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Ware, Jonathan Andrew. "A multi resolution modular sensing system for robotic applications." Thesis, University of South Wales, 1992. https://pure.southwales.ac.uk/en/studentthesis/a-multi-resolution-modular-sensing-system-for-robotic-applications(b7166471-3e4f-4993-9e42-60ebec94dafb).html.
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This thesis documents the research that has led to the development, in prototype form, of a modular sensing system for use in a robot's work cell. The system implemented overcomes one of the major limitations of existing sensing systems, that is the difficulty of altering their sensing characteristics. The majority of sensing systems that are currently available are inflexible in that the addition of extra sensors requires, at the very least, substantial changes to both hardware and software. What these systems require is a facility through which users can easily, and readily, make changes to the configuration of the sensors they employ. In the modular system described, the sensors that provide the information about the robot's work cell are independent of the algorithms that make use of the information. That is, the sensors do not need any knowledge as to when or how the information they provide will be used. Similarly, the algorithms that make use of the data do not need any knowledge as to the provider of the data. This separation of data provider from data user enables the software that controls the sensors (and even the sensors themselves) to be upgraded without corresponding changes to the data user software. Additional sensors can easily be added to the system while redundant sensors can simply be removed. The location of objects within the robot's workspace is achieved by building a model of the workspace using the information provided by a number of sensors. As a prerequisite to model construction three problems had to be addressed. Firstly, the information extracted from different sensors is generally at different resolutions. Secondly, the representation of 3-D space requires large amounts of computer memory. Thirdly, the production of the 3-D model, particularly when a large number of sensors are involved requires a substantial amount of processor time. The first two problems were addressed using a data structure that allowed compact data storage, while the final problem was reduced by identifying parallel aspects of the processing and implementing them on a network of transputers. After the objects within the robot's workspace have been located, the next stage is to identify them. The identification is achieved by calculating the degree of match between measurable characteristics of the object to be identified and the same measurable characteristics of known objects. The degree of match, which is similar but not identical to the correlation function, between the object to be identified and each known object is then used to determine, if possible, the required identity of the object. The work contained within the thesis not only demonstrates the feasibility and benefits of a modular sensing system, over traditional sensing system, but has brought to light some points that will need further thought before a fully functional system is produced. The last chapter contains, in addition to a full and detailed list of conclusions made during the research, a summary of some of these areas that still require further work.
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Pateras, Claudia. "Object identification in mobile robotic applications through dialogue and sensing." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=22787.
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The domain of our work is mobile robotic task execution under dialogue control. In this domain, we examine some of the main issues related to automatic object identification based on a natural language description. In particular, the descriptions are referring expressions, and the goal is to identify the referent through a combination of dialogue and autonomous sensing.The first step in this process involves bridging the gap between the user and system representations of the world. A number of concepts are expressed in natural language by vague terms like "the big box" and "very close to the door". We use fuzzy logic to map these vague terms onto the quantitative sensory data used in the computer representation of the environment. The uncertainty resulting from this mapping is abated by allowing the robotic agent to query the user for more information or to use sensors to collect missing data. We examine the trade-off between querying the user, sensing, and uncertainty in the situations where identification is not immediately realizable. Furthermore, we have devised an efficient questioning strategy based on the use of entropy to select the questions having the greatest discriminatory power over referent candidates. We have developed a framework to deal with each of these issues and have implemented a working system to demonstrate our strategies.
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Wen, Wu. "Multi-sensor geometric estimation." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314911.
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Graham, George M. "On-line laser ultrasonic sensing for control of robotic welding quality." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/16949.
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Rosell, Gratacòs Jan. "Fine-motion planning for robotic assembly under modelling and sensing uncertainties." Doctoral thesis, Universitat Politècnica de Catalunya, 1998. http://hdl.handle.net/10803/5935.
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This thesis proposes a fine-motion planner for assembly tasks in the plane considering two degrees of freedom of translation and one of rotation, taking into account modelling and sensing uncertainties and the effect of friction. The proposed planner is based on a two-phase approach. First, uncertainty is not considered and a nominal solution path is searched in a graph representing the free configuration space, which has been obtained with an exact cell decomposition method. Then, uncertainty is considered and the arcs of the solution path are evaluated in order that the possible contacts occurring during the traversing of the arc do not provoke a failure of the task execution. When this is not possible, the planner finds a patch plan in contact-space in an analogous way as the nominal solution path in free-space.
This work:
- introduces the parametrized translational configuration space, which is an embedding of the rotational degree of freedom into the translational configuration space, for the analysis of the geometric constraints of planar assembly tasks.
- makes a thorough analysis of the sources of uncertainty that affect an assembly task. Modelling and sensing uncertainties have been considered. Although modelling uncertainty is an important source of uncertainty that affects assembly tasks, it has usually been overlooked by most of the researchers. In this work, this source of uncertainty has been meticulously studied, by analyzing the effects of both positioning uncertainty and manufacturing tolerances. The dependence between sources of uncertainty is also taken into account.
- includes a force analysis using the dual representation of forces, which allows to consider in an easy way both the geometric uncertainties that affect the possible raction forces arising at the contact situations, as well as the sensor uncertainties. Friction has been considered and modelled with the generalized friction cone. The suitability of this model for this kind of tasks has been validated from the experiments.
- synthesizes the robot motions using a force-compliant control based on the generalized damping model. Task execution includes uncertainty reduction routines in order to adapt the robot commands to the actual geometry of the task.
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Borgstrom, Per Henrik. "Novel cable-driven robotic platforms and algorithms for environmental sensing applications." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=2025611521&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Aboufadel, Naji. "Machine monitoring sensing and robotic control of a mechanical fragmentation machine." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ37933.pdf.
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Liu, Sandra Q. "Vision-based proprioception of a soft robotic finger with tactile sensing." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127131.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 69-72).
Over the past decade, the development of soft robots has significantly progressed. Today, soft robots have a variety of usages in multiple fields, ranging from surgical robotics to prostheses to human-robot interaction. These robots are more versatile, adaptable, safe, robust, and dexterous than their conventional rigid-body counterparts. However, due to their high-dimensionality and flexibility, they still lack a quintessential human ability: the ability to accurately perceive themselves and the environment around them. To maximize their effectiveness, soft robots should be equipped with both proprioception and exteroception that can capture this intricate high-dimensionality. In this thesis, an embedded vision-based sensor, which can capture richly detailed information, is utilized to concurrently perceive proprioception and tactile sensing. Three proprioceptive methods are implemented: dot pose tracking, lookup table, and deep learning.
Although dot pose tracking (average 0.54 mm RMSE) and the lookup table (0.91 mm accumulative distance error) both have accurate proprioception results, they are impractical to implement and easily influenced by outside parameters. As such, the deep learning method for soft finger proprioception was implemented for the GelFlex, a novel highly underactuated exoskeleton-covered soft finger with embedded cameras. The GelFlex has the ability to perform both proprioception and tactile sensing and upon assembly into a two-finger robotic gripper, was able to successfully perform a bar stock classification task, which requires both types of sensing. The proprioception CNN was extremely accurate on the testing set (99% accuracy where all angles were within 1° error) and had an average accumulative distance error of 0.77 mm during live testing, which is better than human finger proprioception (8.0 cm ±1.0 cm error).
Overall, these techniques allow soft robots to be able to perceive their own shape and the surrounding environment, enabling them to potentially solve various everyday manipulation tasks.
by Sandra Q. Liu.
S.M.
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Barbot, Antoine. "On-chip unthethered helical microrobot for force sensing applications." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS425/document.
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Au cours des dernières décennies, l'étude des puces microfluidiques capables d'exécuter des processus chimiques et biologiques sur quelques centimètres carrés a été un domaine de recherche actif. De telles plateformes offrent un environnement fermé et contrôlable qui permet une mesure reproductible et évite toute contamination externe. Cependant, ces environnements sont fermés, ce qui empêche l'utilisation de sondes de mesure ou d'effecteurs fixés à l'extérieur de la puce microfluidique. Pour répondre à ce besoin, nous proposons d'utiliser des microrobots rotatifs hélicoïdaux évoluant dans un fluide. Les microrobots proposés sont conçus grâce à la lithographie 3D par laser. Ils présentent une forme hélicoïdale de 5.5 µm de diamètre et environ 50 µm de longueur. Une couche mince ferromagnétique déposée sur ces microrobots permet de les propulser et de les contrôler grâce à un champ magnétique tournant homogène.Le premier défi est l'intégration stable de microrobots à l'intérieur d'un environnement microfluidique. Dans cette thèse, nous avons donc d'abord prouvé que ces microrobots peuvent utiliser leur propre mobilité pour s'intégrer individuellement à l'intérieur d'une puce microfluidique en utilisant un microcanal relié à un réservoir ouvert. Pour cela, nous avons développé un mouvement 3D où le microrobot évolue dans le fluide et deux mouvements 2D où il évolue sur une surface. En passant facilement d'un mouvement à l'autre, les microrobots peuvent utiliser les différents avantages de chaque mouvement pour obtenir une mobilité suffisante à cette intégration. Nous avons nommé ce modèle de microrobot "Roll-to-Swimm"(RTS).Ensuite, pour utiliser un microrobot comme capteur de force sur puce microfluidique, il est nécessaire de caractériser la force générée par l'hélice de chaque RTS. Une méthode de caractérisation est proposée, dans laquelle les différents paramètres d'environnement tels que le flux parasite, le gradient de température et l'impact des surfaces, sont contrôlées avec précision grâce à l'environnement microfluidique. Nous en concluons que le modèle de microrobot "RTS" peut appliquer une force de 10 à 45 piconewton avec une erreur maximale de 38 %. La composante principale de cette erreur (73 %) est due à l'évolution de l'aimantation du RTS. Par conséquent, les efforts visant à réduire cette erreur doivent d'abord se concentrer sur la propriété de magnétisation du RTS. Cette erreur peut également être temporairement réduite en caractérisant la RTS juste avant son utilisation dans une expérience.Enfin, nous présentons trois preuves de concept pour démontrer que notre méthode de caractérisation rapproche les microrobots hélicoïdaux des applications potentielles. Tout d'abord, nous mesurons la diminution de la force du RTS lorsqu'il pousse une microbille. Cette mesure est essentielle pour connaitre la force appliquée par le RTS sur un objet ou pour mesurer l'état de surface en utilisant des billes comme interface. Une microbille de 10 µm de diamètre à la pointe du RTS réduit la propulsion de 6 %. Deuxièmement, nous utilisons la caractérisation du RTS pour mesurer la vitesse locale de l'écoulement dans un canal. Puis nous proposons d'utiliser cette mesure de vitesse pour le contrôle du microrobot grâce à un contrôle automatique du RTS qui adapte le type de mouvement en fonction de la vitesse de l'écoulement. Ce contrôle a été testé expérimentalement avec différentes conditions d'écoulement. Troisièmement, nous utilisons la caractérisation du RTS pour effectuer des simulations numériques afin de trouver une stratégie de contrôle dans des microcanaux de taille inférieure à 20 fois le diamètre du RTS. Le modèle de cette simulation a été validé en comparant ces résultats avec des données expérimentales. Finalement, nous proposons un système de contrôle permettant de maintenir le RTS centré à l'intérieur de microcanaux courbes évoluant en 3D, en utilisant seulement une acquisition d'image en 2DMicrofluidic chips that could perform chemical and biological processes on a few centimeter square footprint have been an active area of research in the past decades. Among other advantages, this platform offers a closed and controllable environment that allows reproducible measurements and avoids external contamination. However, such closed environments prevent the use of tethered probes to measure or apply a specific force on an element inside the microfluidic chip. Therefore we propose to use a helical rotating microrobot inside a microfluidic chip to answer this need. The proposed microrobots are designed with 3D laser lithography, and have a helical shape of 5.5 µm in diameter and around 50 µm length. A thin ferromagnetic layer is deposited on these microrobots which allows us to propel and control them with a homogenous external rotating magnetic field.The first challenge is the stable integration of these microrobots inside microfluidic environments. Therefore, in this thesis we first proved that these microrobots can use their own mobility to integrate themselves selectively (one by one) inside a microfluidic chip through a microchannel connected to an open reservoir. For this, we have developed a 3D motion where the microrobot evolves in the fluid and two different 2D motions where it evolves on a surface. By switching easily from one motion to another, the microrobots can use the different advantages of each motion to get sufficient mobility required for this integration. We named our microrobot design Roll-To-Swimm (RTS) in reference to this characteristic.Then in order to use a microrobot as on-chip force sensor, a precise characterization of the force generated by the helical shape is necessary for each RTS. A characterization method is proposed, where the different environment parameters (parasite flow, temperature gradient and impact of near surfaces on the flow) are controlled precisely thanks to the microfluidic environment. The characterization shows that the force range of the RTS is between 10 and 45 piconewton with a maximum error of 38 %. We also conclude that the main component of this error (73 %) is due to the evolution of the RTS magnetization. Therefore the efforts to reduce this error should first focus on the magnetization property of the RTS. This error can also be temporarily reduced by characterizing the RTS just before its use in another experiment.Finally, we present three different proofs of concept to demonstrate that our characterization method brings helical microrobots closer to potential on-chip force sensing applications. Firstly, we show that it is possible to measure the diminution of the RTS force when it is pushing a micro spherical bead. This is essential toward applying force on an object with this RTS or to use beads as an interface between the RTS and the surface to measure friction forces. A microbead with 10 µm in diameter at the tip of the RTS reduces it propulsion of 6 %.Secondly, we use the RTS characterization to measure local flow speed. We demonstrate this feature by measuring flow profiles in fluid channels. We show the potential use for of microrobot control by proposing an automatic control of the RTS that adapts the motion to the measured flow. This control has been tested experimentally with different flow conditions. Thirdly, we use the characterization of the RTS to perform numerical simulations in order to find a control strategy in small microchannels. Indeed we demonstrate that for microchannels below 20 times the RTS diameter, the channel walls have an impact on the RTS motions. The model of this simulation has been validated by comparing this result with experimental data. Finally we propose a control scheme for maintaining the RTS centered in a curved microchannel by only using a 2D image feedback
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Adl, Payman. "Development of a magnetoresistive shear and normal force tactile sensor and its hierarchical test environment." Thesis, Brunel University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304127.
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Gelaky, R. "On the design and development of a modular tactile sensing system." Thesis, University of Reading, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234486.
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Raphael, Roy A. "Robotic manipulation of a moving platform utilizing force sensing and sonar ranging." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA344722.
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Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, March 1998.Thesis advisor(s): Xiaoping Yun, John G. Ciezki. "March 1998." Includes bibliographical references (p. 115-116). Also available online.
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Chua, Ping Yong. "23 DOF anthropomorphic robotic hand with high resolution spatio-temporal tactile sensing." Thesis, University of Salford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492405.
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General purpose robot end-effectors are fast, accurate and on occasions flexible, but inherently narrow in the tasks they perform. In endeavouring to mimic the human hand (the most dexterous end-effector), a tele-operated 5 fingered, 23 degree of freedom (DOF) dexterous anthropomorphic robotic hand has been designed, constructed and tested. This hand is biomimetically actuated by 20 braided pneumatic Muscle Actuators (pMAs). The thesis shows the structured development of this complex anthropomorphic robotics structure, a method of taking advantage of the inherent nature of the pMAs which weakens linearly as it contracts, a system of transmitting power from pMAs to the joints in the robotic hand, a novel method of demonstrating the dexterity and speed of the robotic hand and development of a micro-controller (μC) based pMA controller.
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Luo, Xi. "Motion estimation of a flexible robotic manipulator with vibration and vision sensing." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/43260/.
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Compared to conventional rigid robotic manipulators and unlike traditional industrial robotic manipulators, flexible manipulator can be more efficient and safer to operate due to their low power consumption and lightness. Moreover, the next generation of robots will require compliance to be able to perform safe and close interactions with human beings. However, due to the flexibility in arms and joints, flexible manipulator control and operation suffers from severe structural vibration, leading to the inaccuracy in end-effector trajectory tracking and visual servoing. This research work aims to address the problem by developing a systematic motion estimation methodology for flexible robotic manipulators by using vibration and visual sensing. The aim was achieved by addressing several research objectives that include the investigation of the dynamics characteristics of a flexible robotic manipulator for the end-effector’s motion estimation, the study of decentralized vibration control of a multi-link flexible manipulator with piezoelectric sensor, the development of motion estimation framework experimentally through a single-link flexible manipulator test-rig and also the development the computer vision based motion estimation method for a flexible robotic manipulator with an eye-in-hand configuration. The dynamic characteristics of the flexible manipulator were investigated for development of the end-effector’s motion estimation. This was obtained by incorporating the modelling of flexible manipulator with embedded smart piezoelectric transducer based on co-rotational finite element method. This modelling method allows the simulation of non-linear dynamic motion of a flexible multi-link manipulator undergoing not only large rotations and translations of the manipulator, but also potentially large non-linear structural deformations of flexible links. Numerical simulations were performed on single-link and two-links flexible manipulator embedded with smart piezoelectric transducers. The results have demonstrated that this model could be effectively used to study the motion of end-effector for a multi-link flexible robotic manipulator undergoing complex large motions, while allowing the use of embedded piezoelectric transducers for measuring its structural vibration. In order to suppress the structural vibration of flexible manipulator, a decentralized control scheme based on the voltage rate feedback using pairs of collocated piezoelectric actuator/sensor has been utilized. The numerical case studies of single-link and two-links manipulator have been performed respectively. A special consideration is given for finding the best location for piezoelectric transducers over the multi-link flexible system. Generally speaking, motor encoder measures rigid body motion of the manipulator while vibration signals measure the flexible body motion of flexible manipulator. Thus a Kalman filter is developed as to estimate the motion of end-effector of flexible manipulator with the signals of piezoelectric sensor and motor encoder. The effectiveness of the proposed estimation method is evaluated and demonstrated by the developed co-rotational finite element model. The benefit of this method is that although the motion of flexible manipulator can be highly non-linear due to large rotations, the use of a linear Kalman filter, combined with the encoder information, may be sufficient for the estimation purpose for determining the motion of end-effector. On the other hand, robotics vision sensing has been intensively studied from various aspects in the last decade due to the increasing computational power available for processing images. This work proposes a visual-based motion estimation method for flexible robotic manipulator with an eye-in-hand configuration. The object tracking is proposed based on the autocorrelation method that measures the similarity of features between consecutive frames thus the estimation of corresponding apparent motion. The apparent motion is then combined with the geometry of the calibrated camera allowing deriving the angular position of the flexible arm at high frequency with high accuracy. This kind of method requires minimum computation and suitable for fast vision computation applications. Experimental results performed on the single-link flexible manipulator test rig demonstrated the feasibility of its application in flexible manipulator with eye-in-hand system. The developed vision sensing method obtains more precise information of the end-effector location and it is easy to extend to multiple flexible-link problems. The benefit of using this vision sensing method is that it can provide a direct measurement method without the need of any complex transformation procedures and also can be easily extended to multiple-link flexible manipulator cases without additional measurement devices or sensors.
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Bebek, Ozkan. "ROBOTIC-ASSISTED BEATING HEART SURGERY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1201289393.
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Laferrière, Pascal. "Instrumented Compliant Wrist System for Enhanced Robotic Interaction." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35502.
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This thesis presents the development of an instrumented compliant wrist mechanism which serves as an interface between robotic platforms and their environments in order to detect surface positions and orientations. Although inspired by similar existing devices, additional features such as noncontact distance estimations, a simplified physical structure, and wireless operation were incorporated into the design. The primary role envisioned for this mechanism was for enabling robotic manipulators to perform surface following tasks prior to contact as this was one requirement of a larger project involving inspection of surfaces. The information produced by the compliant wrist system can be used to guide robotic devices in their workspace by providing real-time proximity detection and collision detection of objects.
Compliance in robotic devices has attracted the attention of many researchers due to the multitude of benefits it offers. In the scope of this work, the main advantage of compliance is that it allows rigid structures to come into contact with possibly fragile objects. Combined with instrumentation for detecting the deflections produced by this compliance, closed-loop control can be achieved, increasing the number of viable applications for an initially open-loop system.
Custom fabrication of a prototype device was completed to physically test operation of the designed system. The prototype incorporates a microcontroller to govern the internal operations of the device such as sensor data collection and processing. By performing many computation tasks directly on the device, robotic controllers are able to dedicate more of their time to more important tasks such as path planning and object avoidance by using the pre-conditioned compliant device data.
Extensive work has also gone into the refinement of sensor signals coming from the key infrared distance measurement sensors used in the device. A calibration procedure was developed to decrease inter-sensor variability due to the method of manufacturing of these sensors. Noise reduction in the signals is achieved via a digital filtering process.
The evaluation of the performance of the device is achieved through the collection of a large amount of sensor data for use in characterisation of the sensor and overall system behavior. This comes in the form of a statistical analysis of the sensor outputs to determine signal stability and accuracy. Additionally, the operation of the device is validated by its integration onto a manipulator robot and incorporating the data generated into the robot’s control loop.
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Ohka, Masahiro, Hiroaki Kobayashi, Jumpei Takata, and Yasunaga Mitsuya. "Sensing Precision of an Optical Three-axis Tactile Sensor for a Robotic Finger." IEEE, 2006. http://hdl.handle.net/2237/9504.
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Gu, Jianjun Jason. "Design, sensing and control of a robotic prosthetic eye for natural eye movement." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ60293.pdf.
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Calibo, Taylor K. "Obstacle detection and avoidance on a mobile robotic platform using active depth sensing." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42591.
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Approved for public release; distribution is unlimitedThe ability to recognize and navigate surrounding environments free from collision with obstacles has been at the forefront of mobile robotic applications since its inception. At the price of nearly one tenth of a laser range finder, the Xbox Kinect uses an infrared projector and camera to capture images of its environment in three dimensions. The objective of this thesis was to investigate if the Xbox Kinect can be utilized to detect thin or narrow obstacles that are often invisible to the P3-DX mobile robotic platform. We present an algorithm to process and analyze point cloud data from the Xbox Kinect sensor and transform it into a two-dimensional map of the surrounding environment for further use with the P3-DX. Obstacle avoidance scenarios were then performed using two separate algorithms: a narrow corridor following algorithm and a potential fields algorithm. The results demonstrate that in a structured testing environment, the Xbox Kinect can be used to detect and avoid narrow obstacles that are not immediately recognized by the onboard sonar array of the P3-DX.
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Day, Nathan McClain. "Tactile Sensing and Position Estimation Methods for Increased Proprioception of Soft-Robotic Platforms." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7004.
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Soft robots have the potential to transform the way robots interact with their environment. This is due to their low inertia and inherent ability to more safely interact with the world without damaging themselves or the people around them. However, existing sensing for soft robots has at least partially limited their ability to control interactions with their environment. Tactile sensors could enable soft robots to sense interaction, but most tactile sensors are made from rigid substrates and are not well suited to applications for soft robots that can deform. In addition, the benefit of being able to cheaply manufacture soft robots may be lost if the tactile sensors that cover them are expensive and their resolution does not scale well for manufacturability. Soft robots not only need to know their interaction forces due to contact with their environment, they also need to know where they are in Cartesian space. Because soft robots lack a rigid structure, traditional methods of joint estimation found in rigid robots cannot be employed on soft robotic platforms. This requires a different approach to soft robot pose estimation. This thesis will discuss both tactile force sensing and pose estimation methods for soft-robots. A method to make affordable, high-resolution, tactile sensor arrays (manufactured in rows and columns) that can be used for sensorizing soft robots and other soft bodies isReserved developed. However, the construction results in a sensor array that exhibits significant amounts of cross-talk when two taxels in the same row are compressed. Using the same fabric-based tactile sensor array construction design, two different methods for cross-talk compensation are presented. The first uses a mathematical model to calculate a change in resistance of each taxel directly. The second method introduces additional simple circuit components that enable us to isolate each taxel electrically and relate voltage to force directly. This thesis also discusses various approaches in soft robot pose estimation along with a method for characterizing sensors using machine learning. Particular emphasis is placed on the effectiveness of parameter-based learning versus parameter-free learning, in order to determine which method of machine learning is more appropriate and accurate for soft robot pose estimation. Various machine learning architectures, such as recursive neural networks and convolutional neural networks, are also tested to demonstrate the most effective architecture to use for characterizing soft-robot sensors.
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Siores, E. "Development of a real-time ultrasonic sensing system for automated and robotic welding." Thesis, Brunel University, 1988. http://bura.brunel.ac.uk/handle/2438/5550.
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The implementation of robotic technology into welding processes is made difficult by the inherent process variables of part location, fit up, orientation and repeatability. Considering these aspects, to ensure weld reproducibility consistency and quality, advanced adaptive control techniques are essential. These involve not only the development of adequate sensors for seam tracking and joint recognition but also developments of overall machines with a level of artificial intelligence sufficient for automated welding. The development of such a prototype system which utilizes a manipulator arm, ultrasonic sensors and a transistorised welding power source is outlined. This system incorporates three essential aspects. It locates and tracks the welding seam ensuring correct positioning of the welding head relatively to the joint preparation. Additionally, it monitors the joint profile of the molten weld pool and modifies the relevant heat input parameters ensuring consistent penetration, joint filling and acceptable weld bead shape. Finally, it makes use of both the above information to reconstruct three-dimensional images of the weld pool silhouettes providing in-process inspection capabilities of the welded joints. Welding process control strategies have been incorporated into the system based on quantitative relationships between input parameters and weld bead shape configuration allowing real-time decisions to be made during the process of welding, without the need for operation intervention.
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Baehl, Douglas A. "The application of landmark vision sensing for position feedback in a robotic welding workcell." Thesis, Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/19461.
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Lopez-Juarez, Ismael. "On-line learning for robotic assembly using artificial neural networks and contact force sensing." Thesis, Nottingham Trent University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310849.
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Bekiroglu, Yasemin. "Learning to Assess Grasp Stability from Vision, Touch and Proprioception." Doctoral thesis, KTH, Datorseende och robotik, CVAP, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104035.
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Grasping and manipulation of objects is an integral part of a robot’s physical interaction with the environment. In order to cope with real-world situations, sensor based grasping of objects and grasp stability estimation is an important skill. This thesis addresses the problem of predicting the stability of a grasp from the perceptions available to a robot once fingers close around the object before attempting to lift it. A regrasping step can be triggered if an unstable grasp is identified. The percepts considered consist of object features (visual), gripper configurations (proprioceptive) and tactile imprints (haptic) when fingers contact the object. This thesis studies tactile based stability estimation by applying machine learning methods such as Hidden Markov Models. An approach to integrate visual and tactile feedback is also introduced to further improve the predictions of grasp stability, using Kernel Logistic Regression models. Like humans, robots are expected to grasp and manipulate objects in a goal-oriented manner. In other words, objects should be grasped so to afford subsequent actions: if I am to hammer a nail, the hammer should be grasped so to afford hammering. Most of the work on grasping commonly addresses only the problem of finding a stable grasp without considering the task/action a robot is supposed to fulfill with an object. This thesis also studies grasp stability assessment in a task-oriented way based on a generative approach using probabilistic graphical models, Bayesian Networks. We integrate high-level task information introduced by a teacher in a supervised setting with low-level stability requirements acquired through a robot’s exploration. The graphical model is used to encode probabilistic relationships between tasks and sensory data (visual, tactile and proprioceptive). The generative modeling approach enables inference of appropriate grasping configurations, as well as prediction of grasp stability. Overall, results indicate that the idea of exploiting learning approaches for grasp stability assessment is applicable in realistic scenarios.QC 20121026
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Michell, V. A. S. "An application of structured light techniques to the examination of holes and concavities." Thesis, University of Oxford, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235043.
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Andrews, Emily Katherine 1975. "Elastic elements with embedded actuation and sensing for use in self-transforming robotic planetary explorers." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/88866.
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Sullivan, John, Amy Coffman, Benjamin Roberds, and Jordan Roberts. "Design and Semi-Autonomous Control of a 6-Axis Robotic Arm Used in a Remote Sensing Application." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579692.
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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NVThis paper describes the sensor and actuator package for a 6-axis articulated arm which is part of a robotic vehicle entered in the Mars Rover Challenge competition. The robot is intended to perform some of the same duties as a human, but be remotely controlled. It uses an articulated arm for many of these duties. Because of the large number of degrees of freedom, it would be tedious to control each joint individually. A system was developed to measure the state of each joint, transmit this information back to a base station, and semi-autonomously control the arm.
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Ohka, Masahiro, Hiroaki Kobayashi, and Yasunaga Mitsuya. "Sensing Characteristics of an Optical Three-axis Tactile Sensor Mounted on a Multi-fingered robotic Hand." IEEE, 2005. http://hdl.handle.net/2237/7310.
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Tina, Monteiro Shelsea. "Real Time Measurement of Dirt Pick-up by a Robotic Vacuum Cleaner using Light Sensing Technology." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254349.
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Domestic chores are one of the most tedious and time consuming tasks in a person’s life. A lot of time can be saved and put to better use if these tasks can be automated. One such chore is the routine task of vacuuming the house every day. Robotic vacuum cleaners that clean the house are thus one of the most widely used domestic robots. These robots have the ability to clean the entire house almost autonomously with little or no human intervention. However, most of these robots do not have a system to report the real-time pick up of dirt which can be useful to the user in knowing which parts of his house are dirty and maybe investigate the reason behind it. This information can be useful to the robot as well in determining efficient cleaning patterns based on the dirt localization in the house. In this thesis a prototype was developed to measure the real-time pick-up of dirt by a robotic vacuum cleaner. It uses light sensing technology to measure the amount of dirt picked up and can thus be used to glean which parts of the house are dirtier than the others. The signals can also potentially be used to understand the size of the dirt picked up by the robotic vacuum cleaner. Research was done to investigate the different sensing technologies that can be used and to select the appropriate one. The system was tested and conclusions were made regarding its performance. Additional functions that can be implemented and improvements that can be made have also been suggested as future work.Att städa hemmet är en av de mest tråkiga och tidskrävande uppgifterna i en persons liv. Mycket tid kan sparas och användas bättre om dessa uppgifter kan automatiseras. Robotdammsugare som städar golvet i hemmet är en av de mest använda inhemska robotarna, då dessa robotar har möjlighet att rengöra hela huset nästan autonomt med liten eller ingen mänsklig intervention. De flesta av dessa robotar har dock inte ett system för att rapportera realtidsupphämtning av smuts som kan vara användbart, då användaren kan få reda på vilka delar av huset som är smutsiga och då ha möjlighet att undersöka orsaken bakom. Denna information kan också vara användbart för roboten för att bestämma effektiva rengöringsmönster baserat på lokalisering av smuts i huset. I denna avhandling utvecklades en prototyp för att mäta upptagning av smuts i realtid av en robotdammsugare. Den använder IR-teknik för att mäta mängden smuts som hämtas upp och kan därmed använda informationen för att avgöra vilka delar av huset som är smutsigare än andra. Signalerna kan också potentiellt användas för att förstå storleken på smuts som tas upp. Forskning av olika tekniker utfördes för att kunna välja den mest lämpliga. Systemet testades därefter och slutsatser gjordes avseende dess prestanda. Ytterligare utredningar och förbättringar som kan genomföras har också föreslagits som framtida arbete.
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Estrada, Matthew A. "Design and fabrication of force sensing robotic foot utilizing the volumetric displacement of a hyperelastic polymer." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/74436.
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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 39-40).
This thesis illustrates the fabrication and characterization of a footpad based on an original principle of volumetric displacement sensing. It is intended for use in detecting ground reaction forces in a running quadrupedal robot. The footpad is manufactured as a monolithic, composite structure composed of multi-graded polymers reinforced by glass fiber to increase durability and traction. The volumetric displacement sensing principle utilizes a hyperelastic gel-like pad with embedded magnets and Hall-effect sensors. Normal and shear forces can be detected as contact forces cause the gel-like pad to deform into rigid wells without the need to expose the sensor. A one-time training process using an artificial neural network was used to relate the normal and shear forces with the volumetric displacement sensor output. Two iterations on geometry are prototyped and tested. The first shows the ability to accurately predict normal forces in the Z-axis up to 80 N with a root mean squared error of 6% but little information about shear forces in the X an Y-axis. The second iteration demonstrates an ability to pick up the presence and direction of shear forces up to 40 N but with a root mean squared error of 70%. This project demonstrates a proof-of-concept for a more robust force sensor suitable for use in robotics that requires compliance while interacting with its environment.
by Matthew A. Estrada.
S.B.
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Benton, Thomas Henry. "Two Axis Fixture Calibration Utilizing Industrial Robot Artifact Object Touch Sensing." University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1591268868419905.
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Baleia, José Rodrigo Ferreira. "Haptic robot-environment interaction for self-supervised learning in ground mobility." Master's thesis, Faculdade de Ciências e Tecnologia, 2014. http://hdl.handle.net/10362/12475.
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Dissertação para obtenção do Grau de Mestre em
Engenharia Eletrotécnica e de ComputadoresThis dissertation presents a system for haptic interaction and self-supervised learning mechanisms to ascertain navigation affordances from depth cues. A simple pan-tilt telescopic arm and a structured light sensor, both fitted to the robot’s body frame, provide the required haptic and depth sensory feedback. The system aims at incrementally develop the ability to assess the cost of navigating in natural environments. For this purpose the robot learns a mapping between the appearance of objects, given sensory data provided by the sensor, and their bendability, perceived by the pan-tilt telescopic arm. The object descriptor, representing the object in memory and used for comparisons with other objects, is rich for a robust comparison and simple enough to allow for fast computations. The output of the memory learning mechanism allied with the haptic interaction point evaluation prioritize interaction points to increase the confidence on the interaction and correctly identifying obstacles, reducing the risk of the robot getting stuck or damaged. If the system concludes that the object is traversable, the environment change detection system allows the robot to overcome it. A set of field trials show the ability of the robot to progressively learn which elements of environment are traversable.
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Virga, Salvatore [Verfasser], Nassir [Akademischer Betreuer] Navab, Nassir [Gutachter] Navab, and Danail [Gutachter] Stoyanov. "Multimodal Sensing for Autonomous Robotic Ultrasound Imaging / Salvatore Virga ; Gutachter: Nassir Navab, Danail Stoyanov ; Betreuer: Nassir Navab." München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/1223616878/34.
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Blakemore, Andrea L. (Andrea Leigh). "The design of a Hall Effect force sensing flexure on the front leg of a robotic cheetah." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/69503.
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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 37).
To successfully design and program legged robots, it is important to be able to characterize the forces felt on the moving joints. To achieve this, we designed an easy to implement force sensor that used Hall Effect sensors mounted on a flexure to measure force. The flexure was designed to be compliant in two directions, along the ground normal and shear reaction forces. The Hall Effect sensors were mounted so that the change in position of a magnet on the sensor translated to a change in position. By relating this data, the voltage output of the Hall Effect sensors could be related to force through a calibration matrix. The flexure was prototyped at a large scale of 5 in x 5 in x 7 in. The force sensor behaved as expected in compression but abnormally when encountering large shear forces, causing a discrepancy in the calibration matrix. Moving forward, tightening tolerances on the flexure and modifying the Hall Effect sensor setup to use 2- axis sensing for both compression and shear directions should decrease the error between calculated and actual force measurements, allowing for a reliable calibration matrix to be calculated.
by Andrea L. Blakemore.
S.B.
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Monteiro, Rocha Lima Bruno. "Object Surface Exploration Using a Tactile-Enabled Robotic Fingertip." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39956.
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Exploring surfaces is an essential ability for humans, allowing them to interact with a large variety of objects within their environment. This ability to explore surfaces is also of a major interest in the development of a new generation of humanoid robots, which requires the development of more efficient artificial tactile sensing techniques. The details perceived by statically touching different surfaces of objects not only improve robotic hand performance in force-controlled grasping tasks but also enables the feeling of vibrations on touched surfaces. This thesis presents an extensive experimental study of object surface exploration using biologically-Inspired tactile-enabled robotic fingers. A new multi-modal tactile sensor, embedded in both versions of the robotic fingertips (similar to the human distal phalanx) is capable of measuring the heart rate with a mean absolute error of 1.47 bpm through static explorations of the human skin. A two-phalanx articulated robotic finger with a new miniaturized tactile sensor embedded into the fingertip was developed in order to detect and classify surface textures. This classification is performed by the dynamic exploration of touched object surfaces. Two types of movements were studied: one-dimensional (1D) and two-dimensional (2D) movements. The machine learning techniques - Support Vector Machine (SVM), Multilayer Perceptron (MLP), Random Forest, Extra Trees, and k-Nearest Neighbors (kNN) - were tested in order to find the most efficient one for the classification of the recovered textured surfaces. A 95% precision was achieved when using the Extra Trees technique for the classification of the 1D recovered texture patterns. Experimental results confirmed that the 2D textured surface exploration using a hemispheric tactile-enabled finger was superior to the 1D exploration. Three exploratory velocities were used for the 2D exploration: 30 mm/s, 35 mm/s, and 40 mm/s. The best classification accuracy of the 2D recovered texture patterns was 99.1% and 99.3%, using the SVM classifier, for the two lower exploratory velocities (30 mm/s and 35mm/s), respectively. For the 40 mm/s velocity, the Extra Trees classifier provided a classification accuracy of 99.4%. The results of the experimental research presented in this thesis could be suitable candidates for future development.
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West, Jerry. "Orthoplanar Spring Based Compliant Force/Torque Sensor for Robot Force Control." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6637.
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A compliant force/torque sensor for robot force control has been developed. This thesis presents methods of designing, testing, and implementing the sensor on a robotic system. The sensor uses an orthoplanar spring equipped with Hall-effect sensors to measure one component of force and two moment components. Its unique design allows for simple and cost effective manufacturing, high reliability, and compactness. The device may be used in applications where a robot must control contact forces with its environment, such as in surface cleaning tasks, manipulating doors, and removing threaded fasteners. The compliant design of the sensor improves force control performance and reduces impact forces.
Sensor design considerations are discussed, followed by a discussion of the proposed design concept. Theoretical compliance and stress analysis of the orthoplanar spring is presented that allows for rapid design calculations; these calculations are validated via finite element analysis. A mechanical design method is given which uses the results of the compliance and stress analysis. Transducer design is then addressed by developing a model of the sensor. The design methods are used to design a prototype sensor which is tested to determine its instrument uncertainty. Finally, the sensor is implemented on a robotic platform to test its performance in force control.
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Hyttinen, Emil. "Adaptive Grasping Using Tactile Sensing." Licentiate thesis, KTH, Robotik, perception och lärande, RPL, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-206395.
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Grasping novel objects is challenging because of incomplete object data and because of uncertainties inherent in real world applications. To robustly perform grasps on previously unseen objects, feedback from touch is essential. In our research, we study how information from touch sensors can be used to improve grasping novel objects. Since it is not trivial to extract relevant object properties and deduce appropriate actions from touch sensing, we employ machine learning techniques to learn suitable behaviors. We have shown that grasp stability estimation based on touch can be improved by including an approximate notion of object shape. Further we have devised a method to guide local grasp adaptations based on our stability estimation method. Grasp corrections are found by simulating tactile data for grasps in the vicinity of the current grasp. We present several experiments to demonstrate the applicability of our methods. The thesis is concluded by discussing our results and suggesting potential topics for further research.Att greppa nya föremål är utmanande, både eftersom roboten inte har fullständig information om objekten och på grund av den inneboende osäkerheten i verkliga tillämpningar. Återkoppling från känselsensorer är viktigt för att kunna greppa föremål som inte påträffats tidigare. I vår forskning så studerar vi hur information från känselsensorer kan användas för att förbättra greppandet av nya föremål. Eftersom det är svårt att extrahera relevanta egenskaper om föremål och härleda lämpliga åtgärder, baserat på känselsensorer, så har vi använt maskininlärning för att lära roboten lämpliga beteenden. Vi har visat att uppskattningar av stabiliteten av ett grepp baserat på känselsensorer kan förbättras genom att även använda en grov approximation av föremålets form. Vi har även konstruerat en metod som vägleder lokala justeringar av grepp, baserat på vår metod som uppskattar stabiliteten av ett grepp. Dess justeringar hittas genom att simulera känselsensordata för grepp i närheten av det nuvarande greppet. Vi presenterar flera experiment som demonstrerar tillämpbarheten av våra metoder. Avhandlingen avslutas med en diskussion om våra resultat och förslag på möjliga ämnen för fortsatt forskning.
QC 20170510
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Michael, Andrew Mario. "Circle formation algorithm for autonomous agents with local sensing /." Online version of thesis, 2004. http://hdl.handle.net/1850/12143.
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Srnoyachki, Matthew R. "Automated Drilling Application for Autonomous Airfield Runway Surveying Vehicles: System Design and Validation." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1544537004159348.
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Stanley, Benjamin David. "A comparison of binaural ultrasonic sensing systems." Access electronically, 2003. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20040326.140246/index.html.
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Kemppainen, A. (Anssi). "Adaptive methods for autonomous environmental modelling." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526218519.
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Abstract In this thesis, we consider autonomous environmental modelling, where robotic sensing platforms are utilized in environmental surveying. In order to allow a wide range of different environments, our models must be flexible to the data with some a prior assumptions. Respectively, in order to guide action planning, we need to have a unified sensing quality metric that depends on the prediction quality of our models. Finally, in order to be able to adapt to the observed information, at each iteration of the action planning algorithm, we must be able to provide solutions that aim at minimum travelling time needed to reach a certain level of sensing quality. These are the main topics in this thesis. At the center of our approaches are stationary and non-stationary Gaussian processes based on the assumption that the observed phenomenon is due to the diffusion of white noise, where diffusion kernel anisotropy and scale may vary between locations. For these models, we propose adaptation of diffusion kernels based on a structure tensor approach. Proposed methods are demonstrated with experiments that show, assuming sensor noise is not dominating, our iterative approach is able to return diffusion kernel values close to correct ones. In order to quantify how precise our models are, we propose a mutual information based sensing quality criterion, and prove that the optimal design using our sensing quality provides the best prediction quality for the model. To incorporate localization uncertainty in modelling, we also propose an approach where a posterior model is marginalized over sensing path distribution. The benefit is that this approach implicitly favors actions that result in previously visited or otherwise well-defined areas, meanwhile, maximizing the information gain. Experiments support our claims that our proposed approaches are best when considering predictive distribution quality. In action planning, our approach is to use graph-based approximation algorithms to obtain a certain level of model quality in an efficient way. In order account for spatial dependency and active localization, we propose adaptation methods that map sensing quality to vertex prices in a graph. Experiments demonstrate the benefit of our adaptation methods compared to the action planning algorithms that do not consider these specific featuresTiivistelmä Tässä väitöskirjassa tarkastellaan autonomista ympäristön mallinnusta, missä ympäristön kartoitukseen hyödynnetään robottimittausalustoja. Erilaisia ympäristöjä varten, käytettävien mallien tulee olla joustavia datalle tietyillä a priori oletuksilla. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan. Mukautuakseen uuteen informaatioon, ohjausalgoritmin tulee lisäksi pyrkiä joka iteraatiolla minimoimaan tietyn kartoituksen laadun saavuttava kulkuaika. Nämä ovat tämän väitöskirjan pääaiheet. Tämän väitöskirjan keskiössä ovat sellaiset stationaariset ja ei-stationaariset Gaussin prosessit, jotka perustuvat oletukseen että havaittu ilmiö johtuu valkoisen kohinan diffuusiosta. Diffuusiokernelin anisotrooppisuudelle ja skaalalle sallitaan paikkariippuvaisuus. Tässä väitöskirjassa esitetään näiden mallien mukauttamiseen rakennetensoripohjaisia menetelmiä. Suoritetut kokeet osoittavat, että esitetyt iteratiiviset mukauttamismenetelmät tuottavat lähes oikeita diffuusiokernelien arvoja, olettaen, että sensorikohina ei dominoi mittauksia. Mallien ennustustarkkuuden määrittämiseen esitetään keskinäisinformaatioon perustuva kartoituksen laatumetriikka. Väitöskirjassa todistetaan, että optimaalinen ennustuslaatu saavutetaan käyttämällä esitettyä laatumetriikkaa. Väitöskirjassa esitetään lisäksi laatumetriikka, jossa posteriori malli on marginalisoitu kartoituspolkujen jakauman yli. Tämän avulla voidaan huomioida paikannusepävarmuuden vaikutukset mallinnuksessa. Tällöin etuna on se, että kyseinen laatumetriikka suosii implisiittisesti sellaisia mittausalustojen ohjauksia, jotka johtavat aeimmin kartoitetuille tai helposti ennustettaville alueille samalla maksimoiden informaatiohyödyn. Suoritetut kokeet tukevat väittämiä, että väitöskirjassa esitetyt menetelmät tuottavat parhaan ennustusjakauman laadun. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan. Väitöskirjassa esitetään mukautusmenetelmiä kartoituksen laadun kuvaukseksi graafin solmujen kustannuksiksi. Tämän avulla sallitaan sekä spatiaalinen riippuvuus että aktiivinen paikannus. Mittausalustojen ohjaus vaatii vastaavasti yhtenäisen, mallien ennustuslaadusta riippuvan, kartoituksen laatumetriikan
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Jain, Advait. "Mobile manipulation in unstructured environments with haptic sensing and compliant joints." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45788.
Full textAbstract:
We make two main contributions in this thesis. First, we present our approach to robot manipulation, which emphasizes the benefits of making contact with the world across all the surfaces of a manipulator with whole-arm tactile sensing and compliant actuation at the joints. In contrast, many current approaches to mobile manipulation assume most contact is a failure of the system, restrict contact to only occur at well modeled end effectors, and use stiff, precise control to avoid contact.
We develop a controller that enables robots with whole-arm tactile sensing and compliant actuation at the joints to reach to locations in high clutter while regulating contact forces. We assume
that low contact forces are benign and our controller does not place any penalty on contact forces below a threshold. Our controller only requires haptic sensing, handles multiple contacts across the surface of the manipulator, and does not need an explicit model of the environment prior to contact. It uses model predictive control with a time horizon of length one, and a linear quasi-static mechanical model that it constructs at each time step.
We show that our controller enables both a real and simulated robots to reach goal locations in high clutter with low contact forces. While doing so, the robots bend, compress, slide, and pivot around objects. To enable experiments on real robots, we also developed an inexpensive, flexible, and stretchable tactile sensor and covered large surfaces of two robot arms with these sensors. With an informal experiment, we show that our controller and sensor have the potential to enable robots to manipulate in close proximity to, and in contact with humans while keeping the contact forces low.
Second, we present an approach to give robots common sense about everyday forces in the form of probabilistic data-driven object-centric models of haptic interactions. These models can be shared by different robots for improved manipulation performance. We use pulling open doors, an important task for service robots, as an example to demonstrate our approach.
Specifically, we capture and model the statistics of forces while pulling open doors and drawers. Using a portable custom force and motion capture system, we create a database of forces as human operators pull open doors and drawers in six homes and one office. We then build data-driven
models of the expected forces while opening a mechanism, given knowledge of either its class (e.g, refrigerator) or the mechanism identity (e.g, a particular cabinet in Advait's kitchen). We demonstrate that these models can enable robots to detect anomalous conditions such as a locked door, or collisions between the door and the environment faster and with lower excess force applied to the door compared to methods that do not use a database of forces.