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Добірка наукової літератури з теми "Grasping strategies"

Автор: Grafiati

Опубліковано: 11 січня 2025

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Статті в журналах з теми "Grasping strategies"

Desanghere, L., and J. Marotta. "Gaze strategies and grasping: Complex shapes." Journal of Vision 9, no. 8 (March 21, 2010): 1108. http://dx.doi.org/10.1167/9.8.1108.

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Huang, Xiaoqian, Mohamad Halwani, Rajkumar Muthusamy, Abdulla Ayyad, Dewald Swart, Lakmal Seneviratne, Dongming Gan, and Yahya Zweiri. "Real-time grasping strategies using event camera." Journal of Intelligent Manufacturing 33, no. 2 (January 10, 2022): 593–615. http://dx.doi.org/10.1007/s10845-021-01887-9.

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AbstractRobotic vision plays a key role for perceiving the environment in grasping applications. However, the conventional framed-based robotic vision, suffering from motion blur and low sampling rate, may not meet the automation needs of evolving industrial requirements. This paper, for the first time, proposes an event-based robotic grasping framework for multiple known and unknown objects in a cluttered scene. With advantages of microsecond-level sampling rate and no motion blur of event camera, the model-based and model-free approaches are developed for known and unknown objects’ grasping respectively. The event-based multi-view approach is used to localize the objects in the scene in the model-based approach, and then point cloud processing is utilized to cluster and register the objects. The proposed model-free approach, on the other hand, utilizes the developed event-based object segmentation, visual servoing and grasp planning to localize, align to, and grasp the targeting object. Using a UR10 robot with an eye-in-hand neuromorphic camera and a Barrett hand gripper, the proposed approaches are experimentally validated with objects of different sizes. Furthermore, it demonstrates robustness and a significant advantage over grasping with a traditional frame-based camera in low-light conditions.

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Peckre, Louise R., Anne-Claire Fabre, Julien Hambuckers, Christine E. Wall, lluís Socias-Martínez, and Emmanuelle Pouydebat. "Food properties influence grasping strategies in strepsirrhines." Biological Journal of the Linnean Society 127, no. 3 (February 15, 2019): 583–97. http://dx.doi.org/10.1093/biolinnean/bly215.

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Leferink, Charlotte, Hannah Stirton, and Jonathan Marotta. "Visuomotor strategies for grasping a rotating target." Journal of Vision 15, no. 12 (September 1, 2015): 1151. http://dx.doi.org/10.1167/15.12.1151.

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Bulloch, Melissa C., Steven L. Prime, and Jonathan J. Marotta. "Anticipatory gaze strategies when grasping moving objects." Experimental Brain Research 233, no. 12 (August 20, 2015): 3413–23. http://dx.doi.org/10.1007/s00221-015-4413-7.

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Roby-Brami, Agnès, Sylvie Fuchs, Mounir Mokhtari, and Bernard Bussel. "Reaching and Grasping Strategies in Hemiparetic Patients." Motor Control 1, no. 1 (January 1997): 72–91. http://dx.doi.org/10.1123/mcj.1.1.72.

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Hasegawa, Yasuhisa, Kensaku Kanada, and Toshio Fukuda. "Dexterous manipulation from pinching to power grasping - performance comparison of grasping strategies for different objects." IFAC Proceedings Volumes 36, no. 17 (September 2003): 335–40. http://dx.doi.org/10.1016/s1474-6670(17)33416-x.

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Dzitac, Pavel, and Md Mazid Abdul. "Modeling of an Object Manipulation Motion Planner and Grasping Rules." Applied Mechanics and Materials 278-280 (January 2013): 664–72. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.664.

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This paper presents the development of a Motion Planning Module for object manipulation, which is a part of previously developed robotic grasping and manipulation controller. The Motion Planning Module consists of a sensing processor, decision making module, instinctive controller, motion planner and a planned motion controller. Details related to the design and modelling of the motion planning module have been offered. Results of experiments on human grasping rule, suitable for the grasping and manipulation controller, have been discussed. The output of this research may be useful to those developing motion planning strategies for their grasping and manipulation controllers.

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Touillet, Amélie, Adrienne Gouzien, Marina Badin, Pierrick Herbe, Noël Martinet, Nathanaël Jarrassé, and Agnès Roby-Brami. "Kinematic analysis of impairments and compensatory motor behavior during prosthetic grasping in below-elbow amputees." PLOS ONE 17, no. 11 (November 18, 2022): e0277917. http://dx.doi.org/10.1371/journal.pone.0277917.

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After a major upper limb amputation, the use of myoelectric prosthesis as assistive devices is possible. However, these prostheses remain quite difficult to control for grasping and manipulation of daily life objects. The aim of the present observational case study is to document the kinematics of grasping in a group of 10 below-elbow amputated patients fitted with a myoelectric prosthesis in order to describe and better understand their compensatory strategies. They performed a grasping to lift task toward 3 objects (a mug, a cylinder and a cone) placed at two distances within the reaching area in front of the patients. The kinematics of the trunk and upper-limb on the non-amputated and prosthetic sides were recorded with 3 electromagnetic Polhemus sensors placed on the hand, the forearm (or the corresponding site on the prosthesis) and the ipsilateral acromion. The 3D position of the elbow joint and the shoulder and elbow angles were calculated thanks to a preliminary calibration of the sensor position. We examined first the effect of side, distance and objects with non-parametric statistics. Prosthetic grasping was characterized by severe temporo-spatial impairments consistent with previous clinical or kinematic observations. The grasping phase was prolonged and the reaching and grasping components uncoupled. The 3D hand displacement was symmetrical in average, but with some differences according to the objects. Compensatory strategies involved the trunk and the proximal part of the upper-limb, as shown by a greater 3D displacement of the elbow for close target and a greater forward displacement of the acromion, particularly for far targets. The hand orientation at the time of grasping showed marked side differences with a more frontal azimuth, and a more “thumb-up” roll. The variation of hand orientation with the object on the prosthetic side, suggested that the lack of finger and wrist mobility imposed some adaptation of hand pose relative to the object. The detailed kinematic analysis allows more insight into the mechanisms of the compensatory strategies that could be due to both increased distal or proximal kinematic constraints. A better knowledge of those compensatory strategies is important for the prevention of musculoskeletal disorders and the development of innovative prosthetics.

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Prime, S. L., and J. J. Marotta. "Gaze strategies during visually-guided and memory-guided grasping." Journal of Vision 11, no. 11 (September 23, 2011): 967. http://dx.doi.org/10.1167/11.11.967.

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Дисертації з теми "Grasping strategies"

Devereux, David. "Control strategies for whole arm grasping." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/control-strategies-for-whole-arm-grasping(02ddb06c-3264-46e1-818a-8632b1bb05c4).html.

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Grasping is a useful ability that allows manipulators to restrain objects to a desired location or trajectory. Whole arm grasps are grasps that use the entire surface of the manipulator to apply contacts to an object. The problem of determining the shape of an object and planning a grasp for that object with a snake-like robot are considered in this work. Existing algorithms that attempt to allow robots to plan and perform whole arm grasps are lacking, they either use restrictive assumptions or have unrealistic demands in terms of required hardware. The work presented here allows even the most basic of robots to plan grasps on unknown objects whilst using a minimum of assumptions.The new developed Octograsp algorithm is a method of gaining information regarding the shape of the object to be grasped through tactile information alone. This contact information is processed using an inverse convex hull algorithm to build a model of the object's shape and position. The performance of the algorithms are examined using both simulations and experimental hardware, it is shown that accuracy errors as low as 3.1% can be obtained. The accuracy of the model depends upon factors such as the complexity of the object and the suitability of the robot. Manipulators consisting of a large number of small links with relaxed rotational constraints outperform other configurations. It is also shown that the accuracy can be improved by between 11% and 17% by contacting the object from multiple orientations, whilst also encircling from multiple positions can provide a very large improvement of between 56% to 86%. These methods allow even the coarse contact information provided by the experimental equipment to attain a model with an accuracy error of only 26%.A second novel algorithm is described that uses the information provided from the first algorithm to plan strong grasps over the desired object. The algorithm takes, on average, 25.1 seconds to plan the grasp. The mean strength of the planned grasps is 0.3816 using the wrench ball measure, this is firmly in the very good region. Several robotic configurations, as well as objects, are used to test the performance of the algorithm. The optimal parameters of the algorithm are investigated by using the results of 51030 different tests. It is again shown that robots that consist of a large number of small links and with high rotational ability perform the best.

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Yesudasu, Santheep. "Cοntributiοn à la manipulatiοn de cοlis sοus cοntraintes par un tοrse humanοïde : applicatiοn à la dépaléttisatiοn autοnοme dans les entrepôts lοgistiques". Electronic Thesis or Diss., Normandie, 2024. https://theses.hal.science/tel-04874770.

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Cette thèse de doctorat explore le développement et l'implémentation d'URNik-AI, un système de dépalettisation automatisé basé sur l'intelligence artificielle (IA), conçu pour manipuler des boîtes en carton de tailles et de poids variés à l'aide d'un torse humanoïde à double bras. L'objectif principal est d'améliorer l'efficacité, la précision et la fiabilité des tâches de dépalettisation industrielle grâce à l'intégration de la robotique avancée, de la vision par ordinateur et des techniques d'apprentissage profond.Le système URNik-AI est composé de deux bras robotiques UR10 équipés de capteurs de force/torque à six axes et d'outils de préhension. Une caméra RGB-D ASUS Xtion est montée sur des servomoteurs pan-tilt Dynamixel Pro H42 pour obtenir des images haute résolution et des données de profondeur. Le cadre logiciel comprend ROS Noetic, ROS 2 et le framework MoveIt, permettant une communication fluide et une coordination des mouvements complexes. Ce système assure une haute précision dans la détection, la saisie et la manipulation d'objets dans divers environnements industriels.Une contribution importante de cette recherche est l'implémentation de modèles d'apprentissage profond, tels que YOLOv3 et YOLOv8, pour améliorer les capacités de détection et d'estimation de pose des objets. YOLOv3, entraîné sur un ensemble de données de 807 images, a atteint des scores F1 de 0,81 et 0,90 pour les boîtes à une et plusieurs faces, respectivement. Le modèle YOLOv8 a encore amélioré les performances du système en fournissant des capacités de détection de points clés et de squelettes, essentielles pour la manipulation précise des objets. L'intégration des données de nuage de points pour l'estimation de la pose a assuré une localisation et une orientation précises des boîtes.Les résultats des tests ont démontré la robustesse du système, avec des métriques élevées de précision, rappel et précision moyenne (mAP), confirmant son efficacité. Cette thèse apporte plusieurs contributions significatives au domaine de la robotique et de l'automatisation, notamment l'intégration réussie des technologies robotiques avancées et de l'IA, le développement de techniques innovantes de détection et d'estimation de pose, ainsi que la conception d'une architecture de système polyvalente et adaptable
This PhD thesis explores the development and implementation of URNik-AI, an AI-powered automated depalletizing system designed to handle cardboard boxes of varying sizes and weights using a dual-arm humanoid torso. The primary objective is to enhance the efficiency, accuracy, and reliability of industrial depalletizing tasks through the integration of advanced robotics, computer vision, and deep learning techniques.The URNik-AI system consists of two UR10 robotic arms equipped with six-axis force/torque sensors and gripper tool sets. An ASUS Xtion RGB-D camera is mounted on Dynamixel Pro H42 pan-tilt servos to capture high-resolution images and depth data. The software framework includes ROS Noetic, ROS 2, and the MoveIt framework, enabling seamless communication and coordination of complex movements. This system ensures high precision in detecting, grasping, and handling objects in diverse industrial environments.A significant contribution of this research is the implementation of deep learning models, such as YOLOv3 and YOLOv8, to enhance object detection and pose estimation capabilities. YOLOv3, trained on a dataset of 807 images, achieved F1-scores of 0.81 and 0.90 for single and multi-face boxes, respectively. The YOLOv8 model further advanced the system's performance by providing keypoint and skeleton detection capabilities, which are essential for accurate grasping and manipulation. The integration of point cloud data for pose estimation ensured precise localization and orientation of boxes.Comprehensive testing demonstrated the system's robustness, with high precision, recall, and mean average precision (mAP) metrics confirming its effectiveness. This thesis makes several significant contributions to the field of robotics and automation, including the successful integration of advanced robotics and AI technologies, the development of innovative object detection and pose estimation techniques, and the design of a versatile and adaptable system architecture

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Chidambaram, Prem Sagar. "Grasping strategies for a dexterous hand during teleoperation." 2006. http://etd.utk.edu/2006/ChidambaramPremSagar.pdf.

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Enes, Baptiste Emmanuel Parente. "Actuation Strategies for Underactuated Hands: Better Functionality & Better Anthropomorphism." Master's thesis, 2014. http://hdl.handle.net/10316/27662.

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Dissertação de Mestrado em Engenharia Biomédica apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.
Esta disserta¸c˜ao estuda as melhores estrat´egias de atua¸c˜ao para m˜aos rob´oticas sub atuadas, que garantam uma melhor funcionalidade e um melhor antropomorfismo. Este estudo divide-se em duas partes, a primeira parte foca a capacidade que uma m˜ao tem de agarrar diferentes objectos de diferentes formas, enquanto que a segunda se interessa mais na capacidade de uma m˜ao mimetizar movimentos de uma m˜ao humana. Neste estudo pretende-se responder `as duas seguintes quest˜oes: 1) Como ´e que a estrat´egia de atua¸c˜ao de uma m˜ao afecta a sua funcionalidade em termos de grasping? 2) Como ´e que a estrat´egia de atua¸c˜ao de uma m˜ao afecta o seu antropomorfismo em termos das traject´orias definidas pelos seus dedos? Para a primeira an´alise foram definidas duas m´etricas: A diversidade das grasps, isto ´e, considerando a maior parte das grasps executadas por uma m˜ao humana; e Funcionalidade das grasps, ou seja, considerando apenas as grasps mais usadas por humanos em tarefas di´arias. A segunda an´alise baseou-se numa m´etrica j´a existente, chamada “Grade your hand”, em que ´e calculado um “´Indice de Antropomorfismo”. Para tal, foram definidas e comparadas 16 estrat´egias de atua¸c˜ao face as m´etricas definidas. Os resultados destas an´alises podem ser uma boa orienta¸c˜ao para o design de novas vers˜oes de m˜aos sub atuadas de acordo com as suas funcionalidades em termos de grasps execut´aveis e antropomorfismo.
This work focuses on the best actuation strategies for underactuated robotic hands, for a better functionality and a better anthropomorphism. This study is divided in two parts: the first one focuses on the hands’ capability of grasping, while the second analysis gives more emphasis to the hands’ performance in terms of anthropomorphism. This study intends to answer the following two questions for the underactuated anthropomorphic robotic hands: 1) How does the actuation strategy of these hands affects their functionality in terms of grasping? 2) How the actuation strategy of these hands affects their anthropomorphism in terms of finger trajectories? For the first analysis two metrics were defined based on: Grasp Diversity, i. e., considering almost all the possible grasps by the human hand; and Grasp Functionality, i. e., only considering the highly used grasps by humans in their daily tasks. The second analysis was based on an already existing metric called ‘Grade your hand’, that calculates an “Anthropomorphism Index” for robotic hands. Then, 16 possible actuation strategies were defined and compared based on the defined metrics. Results of these analysis can be a good guideline for designing novel underactuated hands with respect to their functionality in terms of achievable grasps and their anthropomorphism.

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Röthling, Frank [Verfasser]. "Real robot hand grasping using simulation-based optimisation of portable strategies / Frank Röthling." 2007. http://d-nb.info/985935464/34.

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Strnádková, Ivana. "Cesty a strategie žáků 10-12letých při řešení vybraného typu slovních úloh." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-338677.

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Title: Ways and strategies of 10-12 years old pupils when solving selected type of word problems Abstract This Diploma thesis is focused on word problems that, to some extent, make pupils troubles with their solution. In the first theoretical part there are word problems that the work deals with. These are word problems with ant signal, dynamic, complementary, graphic and their characteristics. The next section is about the strategy of solving word problems and work with mistakes. The second part is focused on experiment of all types of word problems that are described in the theoretical part. This experiment is analysed according to strategies of pupils' and teachers' solutions. Those strategies are later described and commented in detail. Key words word problem, solving strategy, mistake, source of mistake, grasping of word problem

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Králová, Michaela. "Komparace žákovských strategií řešení slovních úloh." Doctoral thesis, 2015. http://www.nusl.cz/ntk/nusl-351689.

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Primary intention of this doctoral thesis is to examine the potential of mathematical word problems and comparison of various solving processes of mathematical word problems among pupils. The theoretical part of this thesis is based on definition of the term "problem" and shows how different basic psychological directions approach this concept. This is followed with narrower definition of mathematical problem with particular regards to solving process itself, its phases and factors affecting its success rate. Afterwards, the mathematical problem is put in concrete terms with mathematical word problem and its diagnostic and didactic potential is examined. Using real examples and modifications, this thesis shows concrete task situation and its practical use in teaching. The actual research processed data obtained as a result of active survey focused on analysis of solutions used by pupils, putting emphasis on occurrence and type of a mistake and the moment of its emergence. The target group was pupils of lower primary schools. This research showed significantly higher success rate of pupils lead by constructive approach. Also, it proved false certain beliefs held by some traditionalists especially about the importance of written mathematical word problems, usage of unknowns or using the routine...

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Книги з теми "Grasping strategies"

Australia. Parliament. House of Representatives. Standing Committee for Long Term Strategies. Australia as an information society: Grasping new paradigms : report of the House of Representatives Standing Committee for Long Term Strategies, the Parliament of the Commonwealth of Australia. Canberra: Australian Govt. Pub. Service, 1991.

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Australia. Australia as an information society: Grasping new paradigms : Report of the House of Representatives Standing Committee for Long Term Strategies, the Parliament of the Commonwealth of Australia. Australian Govt. Pub. Service, 1991.

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Schmidt, Randell K. A Guided Inquiry Approach to High School Research. ABC-CLIO, LLC, 2013. http://dx.doi.org/10.5040/9798400660535.

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This book helps educators foster academic success and college readiness: it demonstrates how to instruct high school students to find, process, and think about new information, and then synthesize that knowledge. When students are able to manage topics of high interest by choosing their own subject matter, they learn how to effectively perform pre-collegiate research through a process that they find fun and rewarding. Ideal for high school-level teachers and school librarians, this book provides a unique, holistic approach to guided inquiry that guides students step-by-step through the cognitive, affective, and social processes involved, building critical study skills, time management strategies, collaboration techniques, and communication and presentation skills. A Guided Inquiry Approach to High School Research is derived from a formal research protocol and provides proven techniques and supporting materials that facilitate the process for permitting students to choose their own topic, easily grasping how to search for information, and successfully completing a seemingly daunting research assignment—a process that makes understandings deep and integrative. The included detailed project lessons, student handouts, and rubrics and assessment tools are the result of many years of classroom testing and refinement.

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Частини книг з теми "Grasping strategies"

Deimel, Raphael, and Oliver Brock. "Soft Hands for Reliable Grasping Strategies." In Soft Robotics, 211–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44506-8_18.

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Nechyporenko, Nataliya, Antonio Morales, and Angel P. del Pobil. "Grasping Strategies for Picking Items in an Online Shopping Warehouse." In Intelligent Autonomous Systems 15, 775–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01370-7_60.

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Whitfield, Petronilla. "Grasping Towards Being Present in the Text, Entangling Meaning into Memory." In Teaching Strategies for Neurodiversity and Dyslexia in Actor Training, 150–61. New York : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429458590-11.

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Koldewey, Christian, Jürgen Gausemeier, Roman Dumitrescu, Hans Heinrich Evers, Maximilian Frank, and Jannik Reinhold. "Development Process for Smart Service Strategies: Grasping the Potentials of Digitalization for Servitization." In Management for Professionals, 205–37. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69380-0_12.

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Stuke, Tobias, Thomas Rauschenbach, and Thomas Bartsch. "Development of a Robotic Bin Picking Approach Based on Reinforcement Learning." In Machine Learning for Cyber-Physical Systems, 41–49. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47062-2_5.

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AbstractRobotic bin picking systems aim to automate the feeding process of randomly stored objects in industrial production. Despite being a research field for decades, there is still a gap between research and industrial application. The presented work intends to improve the utilization of bin picking for the industrial manufacturing of electrotechnical components. In this context, the development process of a system approach based on machine learning is stated. First, related work is presented and the research issue is derived. Second, a comparison between major machine learning techniques with respect to bin picking is made and a reinforcement learning approach is chosen for this work. Therein, a neural network learns strategies for grasping objects from bulk material depending on their position in the bin. Based on manifold states in a simulation environment, it is the goal to gain a versatile character of the robot system. In this regard, preselection criteria, discrete action primitives and grasp constraints are defined that incorporate domain knowledge to shorten the training effort.

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Baker, Tawrin. "Christoph Scheiner’s The Eye, that is, The Foundation of Optics (1619): The Role of Contrived Experience at the Intersection of Psychology and Mathematics." In Archimedes, 21–54. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52954-2_2.

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AbstractAccounts of the development of experimental methods (including controls, broadly understood) in the seventeenth century have tended to overlook Aristotelians. Until recently the consensus was that, because of the art-nature distinction and a focus on final causes, Aristotelianism had significant issues incorporating experiments and contrived experiences into the natural sciences, including “middle” sciences such as optics.I argue that this picture relies, in part, on misreading Aristotle’s Posterior Analytics as a treatise on epistemology. In particular, book 2 chapter 19 has been seen as an account of how Aristotle justified grasping the principles of a science based on so-called “common sense” experience. Recent Aristotle scholars have challenged this, instead arguing that this notorious chapter on “Aristotelian induction” is, instead, just a general psychological description of how sensation leads to memory, from memory to experience, and from there to the grasping the universal first principles of either an art or a science. The epistemic justification for those principles, for any particular art or science, is rather more complex and domain-specific.What, then, did early modern Aristotelians in fact present as an account of how to actually grasp the first principles of any particular science? This contribution examines the Jesuit polymath Christoph Scheiner’s 1619 work, The Eye, that is, The Foundation of Optics, in which he argues for the revolutionary position that the retina, not the crystalline lens, is the seat of visual sensation. Scheiner relies on first-hand anatomy, contrived experiences, and experiments to establish at the axioms of optics, but I argue that his Aristotelianism presented no special obstacles to this. What Scheiner means by sensation, memory, and experience in this treatise are complex, and Scheiner’s implementation of control practices is rather sophisticated for the time. In this he was part of a general trend in the seventeenth century, most noticed in anti-Aristotelians such as Francis Bacon, in which we see scientific methodology being examined critically and experimental precepts, including control strategies, developed explicitly.

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Hu, Angang. "Creating and Grasping Strategic Opportunities for China." In Report of Strategic Studies in China (2019), 49–64. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7732-1_4.

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"Grasping the Open School Initiative." In Strategies for Innovators, 5–8. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8010-6_2.

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"Grasping the Context." In Redefining Theory and Practice to Guide Social Transformation, 31–49. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6627-5.ch003.

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Nothing happens in isolation and there is always history and spatiality that mediate the present state of affairs. Social conflicts are historical and geographical in nature, and in order to explore them and transform them, it is necessary to have a method. This chapter offers such a method. Drawing from ethnographic approaches from anthropology, and from practical methods such as Theory U and dynamical systems theory (DST), this chapter offers a dedicated study of a conflict area (Medellin, Colombia), and of how peace knowledge emerges from it. By peace knowledge the authors refer to contextual knowledge of specific peacebuilding and peacekeeping strategies that are rooted and specific to particular cultures and societies. This chapter discusses the method that they have developed to engage with social contexts to both identify the ways communities respond peacefully to conflicts, and to elicit culturally sensitive practices that have the potential to transform violent conflicts.

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Engler, Sarah. "Grasping the Nature of CAPs." In Centrist Anti-Establishment Parties and Their Struggle for Survival, 23–41. Oxford University PressOxford, 2023. http://dx.doi.org/10.1093/oso/9780192873132.003.0002.

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Abstract This chapter provides a systematic classification of centrist anti-establishment parties (CAPs) and discusses their characteristics in more detail. More than 50 percent of all new parties that have successfully competed in Central and Eastern European elections since the early 2000s display high levels of anti-establishment rhetoric and promote ideological positions that are affiliated with neither the radical left nor the radical right and can therefore be considered CAPs. But what do CAPs stand for apart from criticizing the political establishment? The literature remains quite vague in this regard and mainly refers to their alleged ideological emptiness. This chapter empirically investigates CAPs’ political platforms and puts forward two conclusions. First, corruption, indeed, is an important issue in the political strategies of almost all CAPs as it allows them to criticize other parties without attacking the latter’s ideological positions. Second, CAPs often display more distinct ideological profiles than the literature would suggest.

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Тези доповідей конференцій з теми "Grasping strategies"

Liu, Le, Guangye Tian, and Ke Li. "A Novel Control Method Combining Feedforward and Feedback Strategies for Prosthetic Grasping." In 2024 International Conference on Advanced Robotics and Mechatronics (ICARM), 935–40. IEEE, 2024. http://dx.doi.org/10.1109/icarm62033.2024.10715858.

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Orsolino, Romeo, Mykhaylo Marfeychuk, Mario Baggetta, Mariana de Paula Assis Fonseca, Wesley Wimshurst, Francesco Porta, Morgan Clarke, Giovanni Berselli, and Jelizaveta Konstantinova. "Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation." In 2024 20th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), 1–7. IEEE, 2024. http://dx.doi.org/10.1109/mesa61532.2024.10704863.

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Kim, Jinseok, Iksu Choi, Taeyeop Cho, Seungjae Won, KwangEun Ko, Kwang Hee Lee, Sangjun Lee, Gi-Hun Yang, and Dongbum Pyo. "Learning Strategies for Erecting Horizontal Objects via Half-Grasping to Aid Subsequent Tasks." In 2024 24th International Conference on Control, Automation and Systems (ICCAS), 1587–88. IEEE, 2024. https://doi.org/10.23919/iccas63016.2024.10773039.

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De Paola, Vincenzo, Giuseppe Calcagno, Alberto Maria Metelli, and Marcello Restelli. "The Power of Hybrid Learning in Industrial Robotics: Efficient Grasping Strategies with Supervised-Driven Reinforcement Learning." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–9. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650627.

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Leeper, Adam Eric, Kaijen Hsiao, Matei Ciocarlie, Leila Takayama, and David Gossow. "Strategies for human-in-the-loop robotic grasping." In the seventh annual ACM/IEEE international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2157689.2157691.

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Ja, Rainer, Sven R. Schmidt-Rohr, Zhixing Xue, Martin Lösch, and Rüdiger Dillmann. "Learning of probabilistic grasping strategies using Programming by Demonstration." In 2010 IEEE International Conference on Robotics and Automation (ICRA 2010). IEEE, 2010. http://dx.doi.org/10.1109/robot.2010.5509958.

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Geidenstam, S., K. Huebner, D. Banksell, and D. Kragic. "Learning of 2D grasping strategies from box-based 3D object approximations." In Robotics: Science and Systems 2009. Robotics: Science and Systems Foundation, 2009. http://dx.doi.org/10.15607/rss.2009.v.002.

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Jia, Shu. "Essence and Strategies of Grasping the Emotional Tone of the Dance." In Proceedings of the 2nd International Conference on Art Studies: Science, Experience, Education (ICASSEE 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icassee-18.2018.134.

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Lin, Jui-An, and Chen-Chien Hsu. "Robotic Grasping Strategies Based on Classification of Orientation State of Objects." In 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW). IEEE, 2021. http://dx.doi.org/10.1109/icce-tw52618.2021.9602960.

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Turco, Enrico, Valerio Bo, Mehrdad Tavassoli, Maria Pozzi, and Domenico Prattichizzo. "Learning Grasping Strategies for a Soft Non-Anthropomorphic Hand from Human Demonstrations." In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE, 2022. http://dx.doi.org/10.1109/ro-man53752.2022.9900669.

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