Relevant bibliographies by topics / Robotic sensing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Robotic sensing'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Robotic sensing"

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Bogue, Robert. "Recent developments in robotic tactile perception." Industrial Robot: An International Journal 44, no. 5 (August 21, 2017): 565–70. http://dx.doi.org/10.1108/ir-06-2017-0106.

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Purpose This paper aims to provide details of recent developments in robotic tactile sensing. Design/methodology/approach Following a short introduction, this paper first provides an overview of tactile sensing effects and technologies. It then discusses recent developments in tactile sensing skins. Tactile sensing for robotic prosthetics and hands is then considered and is followed by a discussion of “tactile intelligence”. Various experimental results are included. Finally, brief concluding comments are drawn. Findings This shows that many advanced, sensitive and technologically varied tactile sensing devices are being developed. These devices are expected to impart robots with a range of enhanced capabilities such as improved gripping and manipulation, object recognition, the control and robotic hands and prosthetics and collision detection. Originality/value Tactile sensing has an increasingly important role to play in robotics, and this paper provides a technical insight into a number of recent developments and their applications.
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Bogue, Robert. "Tactile sensing for surgical and collaborative robots and robotic grippers." Industrial Robot: the international journal of robotics research and application 46, no. 1 (January 21, 2019): 1–6. http://dx.doi.org/10.1108/ir-12-2018-0255.

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Purpose This paper aims to illustrate the increasingly important role played by tactile sensing in robotics by considering three specific fields of application. Design/methodology/approach Following a short introduction, this paper first provides details of tactile sensing principles, technologies, products and research. The following sections consider tactile sensing applications in robotic surgery, collaborative robots and robotic grippers. Finally, brief conclusions are drawn. Findings Tactile sensors are the topic of an extensive and technologically diverse research effort, with sensing skins attracting particular attention. Many products are now available commercially. New generations of surgical robots are emerging which use tactile sensing to provide haptic feedback, thereby eliminating the surgeon’s total reliance on visual control. Many collaborative robots use tactile and proximity sensing as key safety mechanisms and some use sensing skins. Some skins can detect both human proximity and physical contact. Sensing skins that can be retrofitted have been developed. Commercial tactile sensors have been incorporated into robotic grippers, notably anthropomorphic types, and allow the handling of delicate objects and those with varying shapes and sizes. Tactile sensing uses will inevitably increase because of the ever-growing numbers of robots interacting with humans. Originality/value This study provides a detailed account of the growing use of tactile sensing in robotics in three key areas of application.
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Zhang, Feitian, Francis D. Lagor, Hong Lei, Xiaobo Tan, and Derek A. Paley. "Robotic Fish." Mechanical Engineering 138, no. 03 (March 1, 2016): S2—S5. http://dx.doi.org/10.1115/1.2016-mar-6.

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This article reviews different research and development work on robotic fishes. The Collective Dynamics and Control Laboratory at the University of Maryland has constructed two robotic fish to study bio-inspired flow sensing and control of underwater vehicles. Bio-inspired flow sensing and flow-relative control using distributed sensor measurements have been described and demonstrated with two underwater robots. Prototypes of the robotic fish have been designed for experiments to include a rigid airfoil-shaped robot and a flexible, self-propelled robot. The closed-loop control of the flexible robot comprised feedforward and feedback controls. The feedforward term accelerates the convergence of the tracking control, and the feedback term improves the tracking performance by reducing the steady-state error. Rheotaxis and speed-control experiments have demonstrated the effectiveness of the flow sensing and control algorithms. In ongoing work, teams are investigating a novel actuation approach using an internal reaction wheel for flexible fish propulsion.
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Taylor, P. M. "Sensing in Advanced Robotic Assembly." Measurement and Control 23, no. 2 (March 1990): 43–47. http://dx.doi.org/10.1177/002029409002300203.

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Zhu, Lingfeng, Yancheng Wang, Deqing Mei, and Chengpeng Jiang. "Development of Fully Flexible Tactile Pressure Sensor with Bilayer Interlaced Bumps for Robotic Grasping Applications." Micromachines 11, no. 8 (August 12, 2020): 770. http://dx.doi.org/10.3390/mi11080770.

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Flexible tactile sensors have been utilized in intelligent robotics for human-machine interaction and healthcare monitoring. The relatively low flexibility, unbalanced sensitivity and sensing range of the tactile sensors are hindering the accurate tactile information perception during robotic hand grasping of different objects. This paper developed a fully flexible tactile pressure sensor, using the flexible graphene and silver composites as the sensing element and stretchable electrodes, respectively. As for the structural design of the tactile sensor, the proposed bilayer interlaced bumps can be used to convert external pressure into the stretching of graphene composites. The fabricated tactile sensor exhibits a high sensing performance, including relatively high sensitivity (up to 3.40% kPa−1), wide sensing range (200 kPa), good dynamic response, and considerable repeatability. Then, the tactile sensor has been integrated with the robotic hand finger, and the grasping results have indicated the capability of using the tactile sensor to detect the distributed pressure during grasping applications. The grasping motions, properties of the objects can be further analyzed through the acquired tactile information in time and spatial domains, demonstrating the potential applications of the tactile sensor in intelligent robotics and human-machine interfaces.
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Liu, Ji Zhong, Ru Yuan Ma, Yuan Bin Mo, and Ming Liang Jin. "A Simple Deterministic 0-1 Measurement Matrix for Robotic Embedded Vision Compressed Sensing." Applied Mechanics and Materials 433-435 (October 2013): 257–60. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.257.

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Embedded environmental vision is a key issue for robotics. However, the image data is large, which usually will seriously affect the system processing speed and performance. Aiming at the feasibility and the real-time performance of robotic embedded vision system, by combining the up-to-date compressed sensing technology, a novel wavelet sparsity based simple deterministic 0-1 measurement matrix (0-1SDMM) is designed. The simulation results in matlab environment show that the 0-1SDMM has better performance than traditional Gaussian matrix in reconstruction result and reconstruction time. It provides an important reference for the future robotic embedded vision system.
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Dissanayake, Gamini. "Introduction." Robotica 19, no. 5 (August 29, 2001): 465–66. http://dx.doi.org/10.1017/s026357470100340x.

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Field robotics is the use of autonomous robotic systems in highly challenging applications areas including; mining, construction, cargo handling, agriculture, subsea and aerospace systems. The focus of field robotics research is on large-scale outdoor autonomous systems in applications that are characterised by relatively unstructured, difficult and often hazardous environments. It draws together the most advanced research areas in robotics, including; navigation and control, sensing and data fusion, safety and reliability, and planning and logistics.
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Molton, Nicholas, Stephen Se, Michael Brady, David Lee, and Penny Probert. "Robotic sensing for the partially sighted." Robotics and Autonomous Systems 26, no. 2-3 (February 1999): 185–201. http://dx.doi.org/10.1016/s0921-8890(98)00068-2.

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Nguyen, Minh T., and Hamid R. Boveiri. "Energy-efficient sensing in robotic networks." Measurement 158 (July 2020): 107708. http://dx.doi.org/10.1016/j.measurement.2020.107708.

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Tairych, Andreas, and Iain A. Anderson. "Capacitive Stretch Sensing for Robotic Skins." Soft Robotics 6, no. 3 (June 2019): 389–98. http://dx.doi.org/10.1089/soro.2018.0055.

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Dissertations / Theses on the topic "Robotic sensing"

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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 viscoélastique
Tactile 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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Books on the topic "Robotic sensing"

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Dahiya, Ravinder S., and Maurizio Valle. Robotic Tactile Sensing. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1.

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NATO Advanced Research Workshop on Highly Redundant Sensing in Robotic Systems (1988 Il Ciocco, Italy). Highly redundant sensing in robotic systems. Berlin: Springer-Verlag, 1990.

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Tou, Julius T. Highly Redundant Sensing in Robotic Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990.

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Dahiya, Ravinder S. Robotic Tactile Sensing: Technologies and System. Dordrecht: Springer Netherlands, 2013.

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Tou, Julius T., and Jens G. Balchen, eds. Highly Redundant Sensing in Robotic Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84051-7.

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Janabi-Sharifi, Farrokh, and William Melek, eds. Advances in Motion Sensing and Control for Robotic Applications. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17369-2.

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Paley, Derek A., and Norman M. Wereley, eds. Bioinspired Sensing, Actuation, and Control in Underwater Soft Robotic Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50476-2.

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Driels, Morris. Adaptive control of direct drive dexterous robotic hand with bilateral tactile sensing. Monterey, Calif: Naval Postgraduate School, 1990.

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universitet, Örebro, IEEE Instrumentation and Measurement Society. TC-15--Virtual Systems in Measurements., IEEE Instrumentation and Measurement Society. TC-27--Human-Computer Interfaces and Interaction., and IEEE Instrumentation and Measurement Society. TC-28--Instrumentation for Robotics & Automation., eds. ROSE' 03: 1st IEEE International Workshop on Robotic Sensing 2003 : Sensing and perception in 21st century robotics : Örebro University, Örebro, Sweden, 5-6 of June, 2003. Piscataway, N.J: IEEE, 2003.

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Siores, Elias. Development of a real-time ultrasonic sensing system for automated and robotic welding. Uxbridge: Brunel University, 1988.

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Book chapters on the topic "Robotic sensing"

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Dahiya, Ravinder S., and Maurizio Valle. "Human Tactile Sensing." In Robotic Tactile Sensing, 19–41. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_3.

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Dahiya, Ravinder S., and Maurizio Valle. "Tactile Sensing Technologies." In Robotic Tactile Sensing, 79–136. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_5.

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Dahiya, Ravinder S., and Maurizio Valle. "Touch Sensing—Why and Where?" In Robotic Tactile Sensing, 3–12. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_1.

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Dahiya, Ravinder S., and Maurizio Valle. "Tactile Sensing: Definitions and Classification." In Robotic Tactile Sensing, 13–17. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_2.

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Dahiya, Ravinder S., and Maurizio Valle. "System Issues, Requirements and Expectations." In Robotic Tactile Sensing, 43–78. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_4.

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Dahiya, Ravinder S., and Maurizio Valle. "Integrated Tactile Sensing on Silicon." In Robotic Tactile Sensing, 139–52. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_6.

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Dahiya, Ravinder S., and Maurizio Valle. "POSFET I—The Touch Sensing Device." In Robotic Tactile Sensing, 153–75. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_7.

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Dahiya, Ravinder S., and Maurizio Valle. "POSFET II—The Tactile Sensing Chip." In Robotic Tactile Sensing, 177–94. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-0579-1_8.

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Caglioti, Vincenzo, Massimo Danieli, and Domenico Sorrenti. "Sensing Strategies Generation For Monitoring Robot Assembly Programs." In Robotic Systems, 479–86. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2526-0_55.

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Gimple, M., and B. A. Auld. "Capacitive Arrays for Robotic Sensing." In Review of Progress in Quantitative Nondestructive Evaluation, 737–43. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1893-4_83.

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Conference papers on the topic "Robotic sensing"

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Hutchison, John, Gene Klager, Edward McCoy, David Fite, and Brian Frederick. "Robotic Mounted Detection System: robotics for route clearance." In SPIE Defense, Security, and Sensing, edited by Grant R. Gerhart, Douglas W. Gage, and Charles M. Shoemaker. SPIE, 2010. http://dx.doi.org/10.1117/12.852447.

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Trivedi, Deepak, and Christopher D. Rahn. "Shape Sensing for Soft Robotic Manipulators." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87598.

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Soft robotic manipulators are continuum robots made of soft materials that undergo continuous elastic deformation and produce motion with a smooth backbone curve. These manipulators offer significant advantages over traditional manipulators due to their ability to conform to their surroundings, move with dexterity and manipulate objects of widely varying size using whole arm manipulation. Theoretically, soft robots have infinite degrees of freedom (dof), but the number of sensors and actuators are limited. Many dofs of soft robots are not directly observable and/or controllable, complicating shape sensing and controlling. In this paper, we present two methods of shape sensing for soft robotic manipulators based on a geometrically exact mechanical model. The first method use s load cells mounted at the base of the manipulator and the second method makes use of cable encoders running through the length of the manipulator. Simulation results show an endpoint localization error of less than 3% of manipulator length.
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Tai, Heng-Ming, and Yu-Che Chen. "Learning control of robotic manipulators." In Aerospace Sensing, edited by Steven K. Rogers. SPIE, 1992. http://dx.doi.org/10.1117/12.140034.

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Szczerba, Robert J., and Blair R. Collier. "Bounding overwatch operations for robotic and semi-robotic ground vehicles." In Aerospace/Defense Sensing and Controls, edited by Grant R. Gerhart and Ben A. Abbott. SPIE, 1998. http://dx.doi.org/10.1117/12.317552.

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Sanchez, Sean R., and Sean B. Andersson. "Using Compressive Sensing With In-Air Ultrasonic Measurements for Robotic Mapping." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9140.

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Robotic mapping and simultaneous localization and mapping (SLAM) typically rely on sensors that produce a large number of measurements at many locations in an environment to produce an accurate map and, in the case of SLAM, the pose of the robot in that map. However, with the advent of small, low-power robots with insect-scale features, there is a need for techniques that can produce useful maps using limited capability sensors and a small number of measurements. In this work, we focus on the use of compressive sensing to extract local environment reconstructions from ultrasonic sensor measurements. We first examine a simplistic setting where a square pulse is emitted and use the returned echoes in a compressive sensing scheme to reconstruct the locations of objects inside the sensing cone. We then extend this to the more practical setting, accounting for the wave nature of the acoustic signal and corresponding issues of interference, showing that these can be accounted for in designing the measurement matrix of the compressive sensing description of the problem. We demonstrate the performance of our approach though several simulations.
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Blackmore, Simon. "Towards robotic agriculture." In SPIE Commercial + Scientific Sensing and Imaging, edited by John Valasek and J. Alex Thomasson. SPIE, 2016. http://dx.doi.org/10.1117/12.2234051.

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Wells, Peter. "Remote robotic countermine systems." In SPIE Defense, Security, and Sensing, edited by Russell S. Harmon, John H. Holloway, Jr., and J. Thomas Broach. SPIE, 2010. http://dx.doi.org/10.1117/12.850324.

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Proctor, F., Marek Franaszek, and J. Michaloski. "Tolerances and Uncertainty in Robotic Systems." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70404.

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The ability to be programmed for a wide range of tasks is what differentiates robots from dedicated automation. Consequently, robots can be faced with often-changing requirements and conditions. Conventional application development based on teach programming takes robots out of production and occupies personnel, limiting robots’ effectiveness in these environments. Off-line programming solves these problems, but robot inaccuracy must be compensated by a combination of calibration, compliance, and sensing. This complicates up-front systems engineering and application development, but results in systems that can operate in a wider range of requirements and conditions. Performance can be optimized if application tolerances and process uncertainties are known. If they often change, optimization must be done dynamically. Automating this optimization is a goal of smart manufacturing. With its trend of increasing connectivity between the components of robotic systems both within workcells and to the enterprise, exchanging this information has become more important. This includes tolerance information from design through process planning to production and inspection, and measurement uncertainty from sensors into operations. Standards such as ISO 10303 (STEP), the Quality Information Framework (QIF), the Robot Operating System (ROS), and MT-Connect support this exchange to varying degrees. Examples include the assignment of assembly tasks based on part tolerances and robot capabilities; the automated generation of robot paths with tolerances arising from sensed obstacles; and the optimization of part placement to minimize the effects of position uncertainty. This paper examines requirements for exchanging tolerance and uncertainty in robotics applications, identifies how these requirements are being met by existing standards, and suggests improvements to enable more automated information exchange.
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Schoenwald, J. S. "Strategies for Robotic Sensing Using Acoustics." In IEEE 1985 Ultrasonics Symposium. IEEE, 1985. http://dx.doi.org/10.1109/ultsym.1985.198555.

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Han, Xinyu, Liandong Zhang, and Changjiu Zhou. "Robotic arm force sensing interaction control." In 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2012. http://dx.doi.org/10.1109/iciea.2012.6360776.

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Reports on the topic "Robotic sensing"

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Cutkosky, Mark R., Gregory T. Kovacs, Robert D. Howe, Roger Brockett, and Roland Johansson. Tactile Sensing and Control in Humans and Robotic/Teleoperated Systems. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada267710.

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Driels, Morris R. Adaptive Control of Direct Drive Dexterous Robotic Hand with Bilateral Tactile Sensing. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada233980.

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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Brock, D. L. Contact sensing palm for the Salisbury robot hand. Office of Scientific and Technical Information (OSTI), July 1990. http://dx.doi.org/10.2172/6529634.

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Latombe, J. C., A. Lazanas, and S. Shekhar. Robot Motion Planning with Uncertainty in Control and Sensing. Fort Belvoir, VA: Defense Technical Information Center, November 1989. http://dx.doi.org/10.21236/ada323613.

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Bostelman, Roger. Electrical design of the infraredultrasonic sensing for a robot gripper. Gaithersburg, MD: National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.ir.89-4223.

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Edsinger-Gonzales, Aaron. Design of a Compliant and Force Sensing Hand for a Humanoid Robot. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada434151.

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Xavier, P. G., R. G. Brown, and P. A. Watterberg. Coordinating robot motion, sensing, and control in plans. LDRD project final report. Office of Scientific and Technical Information (OSTI), August 1997. http://dx.doi.org/10.2172/527563.

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Spelt, P. F., and H. W. Harvey. Enhanced control & sensing for the REMOTEC ANDROS Mk VI robot. Final report. Office of Scientific and Technical Information (OSTI), August 1997. http://dx.doi.org/10.2172/508111.

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Spelt, P. F., and H. W. Harvey. Enhanced control and sensing for the REMOTEC ANDROS Mk VI robot. CRADA final report. Office of Scientific and Technical Information (OSTI), August 1998. http://dx.doi.org/10.2172/661618.

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