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Artykuły w czasopismach na temat "Grasping strategies"
Desanghere, L., i J. Marotta. "Gaze strategies and grasping: Complex shapes". Journal of Vision 9, nr 8 (21.03.2010): 1108. http://dx.doi.org/10.1167/9.8.1108.
Pełny tekst źródłaHuang, Xiaoqian, Mohamad Halwani, Rajkumar Muthusamy, Abdulla Ayyad, Dewald Swart, Lakmal Seneviratne, Dongming Gan i Yahya Zweiri. "Real-time grasping strategies using event camera". Journal of Intelligent Manufacturing 33, nr 2 (10.01.2022): 593–615. http://dx.doi.org/10.1007/s10845-021-01887-9.
Pełny tekst źródłaPeckre, Louise R., Anne-Claire Fabre, Julien Hambuckers, Christine E. Wall, lluís Socias-Martínez i Emmanuelle Pouydebat. "Food properties influence grasping strategies in strepsirrhines". Biological Journal of the Linnean Society 127, nr 3 (15.02.2019): 583–97. http://dx.doi.org/10.1093/biolinnean/bly215.
Pełny tekst źródłaLeferink, Charlotte, Hannah Stirton i Jonathan Marotta. "Visuomotor strategies for grasping a rotating target." Journal of Vision 15, nr 12 (1.09.2015): 1151. http://dx.doi.org/10.1167/15.12.1151.
Pełny tekst źródłaBulloch, Melissa C., Steven L. Prime i Jonathan J. Marotta. "Anticipatory gaze strategies when grasping moving objects". Experimental Brain Research 233, nr 12 (20.08.2015): 3413–23. http://dx.doi.org/10.1007/s00221-015-4413-7.
Pełny tekst źródłaRoby-Brami, Agnès, Sylvie Fuchs, Mounir Mokhtari i Bernard Bussel. "Reaching and Grasping Strategies in Hemiparetic Patients". Motor Control 1, nr 1 (styczeń 1997): 72–91. http://dx.doi.org/10.1123/mcj.1.1.72.
Pełny tekst źródłaHasegawa, Yasuhisa, Kensaku Kanada i Toshio Fukuda. "Dexterous manipulation from pinching to power grasping - performance comparison of grasping strategies for different objects". IFAC Proceedings Volumes 36, nr 17 (wrzesień 2003): 335–40. http://dx.doi.org/10.1016/s1474-6670(17)33416-x.
Pełny tekst źródłaDzitac, Pavel, i Md Mazid Abdul. "Modeling of an Object Manipulation Motion Planner and Grasping Rules". Applied Mechanics and Materials 278-280 (styczeń 2013): 664–72. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.664.
Pełny tekst źródłaTouillet, Amélie, Adrienne Gouzien, Marina Badin, Pierrick Herbe, Noël Martinet, Nathanaël Jarrassé i Agnès Roby-Brami. "Kinematic analysis of impairments and compensatory motor behavior during prosthetic grasping in below-elbow amputees". PLOS ONE 17, nr 11 (18.11.2022): e0277917. http://dx.doi.org/10.1371/journal.pone.0277917.
Pełny tekst źródłaPrime, S. L., i J. J. Marotta. "Gaze strategies during visually-guided and memory-guided grasping". Journal of Vision 11, nr 11 (23.09.2011): 967. http://dx.doi.org/10.1167/11.11.967.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaYesudasu, 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.
Pełny tekst źródłaThis 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
Chidambaram, Prem Sagar. "Grasping strategies for a dexterous hand during teleoperation". 2006. http://etd.utk.edu/2006/ChidambaramPremSagar.pdf.
Pełny tekst źródłaEnes, Baptiste Emmanuel Parente. "Actuation Strategies for Underactuated Hands: Better Functionality & Better Anthropomorphism". Master's thesis, 2014. http://hdl.handle.net/10316/27662.
Pełny tekst źródłaEsta 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.
Röthling, Frank [Verfasser]. "Real robot hand grasping using simulation-based optimisation of portable strategies / Frank Röthling". 2007. http://d-nb.info/985935464/34.
Pełny tekst źródłaStrnádková, Ivana. "Cesty a strategie žáků 10-12letých při řešení vybraného typu slovních úloh". Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-338677.
Pełny tekst źródłaKrálová, Michaela. "Komparace žákovských strategií řešení slovních úloh". Doctoral thesis, 2015. http://www.nusl.cz/ntk/nusl-351689.
Pełny tekst źródłaKsiążki na temat "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.
Znajdź pełny tekst źródłaAustralia. 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.
Znajdź pełny tekst źródłaSchmidt, Randell K. A Guided Inquiry Approach to High School Research. ABC-CLIO, LLC, 2013. http://dx.doi.org/10.5040/9798400660535.
Pełny tekst źródłaCzęści książek na temat "Grasping strategies"
Deimel, Raphael, i Oliver Brock. "Soft Hands for Reliable Grasping Strategies". W Soft Robotics, 211–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44506-8_18.
Pełny tekst źródłaNechyporenko, Nataliya, Antonio Morales i Angel P. del Pobil. "Grasping Strategies for Picking Items in an Online Shopping Warehouse". W Intelligent Autonomous Systems 15, 775–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01370-7_60.
Pełny tekst źródłaWhitfield, Petronilla. "Grasping Towards Being Present in the Text, Entangling Meaning into Memory". W 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.
Pełny tekst źródłaKoldewey, Christian, Jürgen Gausemeier, Roman Dumitrescu, Hans Heinrich Evers, Maximilian Frank i Jannik Reinhold. "Development Process for Smart Service Strategies: Grasping the Potentials of Digitalization for Servitization". W Management for Professionals, 205–37. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69380-0_12.
Pełny tekst źródłaStuke, Tobias, Thomas Rauschenbach i Thomas Bartsch. "Development of a Robotic Bin Picking Approach Based on Reinforcement Learning". W 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.
Pełny tekst źródłaBaker, 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". W Archimedes, 21–54. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52954-2_2.
Pełny tekst źródłaHu, Angang. "Creating and Grasping Strategic Opportunities for China". W 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.
Pełny tekst źródła"Grasping the Open School Initiative". W Strategies for Innovators, 5–8. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8010-6_2.
Pełny tekst źródła"Grasping the Context". W 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.
Pełny tekst źródłaEngler, Sarah. "Grasping the Nature of CAPs". W 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.
Pełny tekst źródłaStreszczenia konferencji na temat "Grasping strategies"
Liu, Le, Guangye Tian i Ke Li. "A Novel Control Method Combining Feedforward and Feedback Strategies for Prosthetic Grasping". W 2024 International Conference on Advanced Robotics and Mechatronics (ICARM), 935–40. IEEE, 2024. http://dx.doi.org/10.1109/icarm62033.2024.10715858.
Pełny tekst źródłaOrsolino, Romeo, Mykhaylo Marfeychuk, Mario Baggetta, Mariana de Paula Assis Fonseca, Wesley Wimshurst, Francesco Porta, Morgan Clarke, Giovanni Berselli i Jelizaveta Konstantinova. "Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation". W 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.
Pełny tekst źródłaKim, Jinseok, Iksu Choi, Taeyeop Cho, Seungjae Won, KwangEun Ko, Kwang Hee Lee, Sangjun Lee, Gi-Hun Yang i Dongbum Pyo. "Learning Strategies for Erecting Horizontal Objects via Half-Grasping to Aid Subsequent Tasks". W 2024 24th International Conference on Control, Automation and Systems (ICCAS), 1587–88. IEEE, 2024. https://doi.org/10.23919/iccas63016.2024.10773039.
Pełny tekst źródłaDe Paola, Vincenzo, Giuseppe Calcagno, Alberto Maria Metelli i Marcello Restelli. "The Power of Hybrid Learning in Industrial Robotics: Efficient Grasping Strategies with Supervised-Driven Reinforcement Learning". W 2024 International Joint Conference on Neural Networks (IJCNN), 1–9. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650627.
Pełny tekst źródłaLeeper, Adam Eric, Kaijen Hsiao, Matei Ciocarlie, Leila Takayama i David Gossow. "Strategies for human-in-the-loop robotic grasping". W the seventh annual ACM/IEEE international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2157689.2157691.
Pełny tekst źródłaJa, Rainer, Sven R. Schmidt-Rohr, Zhixing Xue, Martin Lösch i Rüdiger Dillmann. "Learning of probabilistic grasping strategies using Programming by Demonstration". W 2010 IEEE International Conference on Robotics and Automation (ICRA 2010). IEEE, 2010. http://dx.doi.org/10.1109/robot.2010.5509958.
Pełny tekst źródłaGeidenstam, S., K. Huebner, D. Banksell i D. Kragic. "Learning of 2D grasping strategies from box-based 3D object approximations". W Robotics: Science and Systems 2009. Robotics: Science and Systems Foundation, 2009. http://dx.doi.org/10.15607/rss.2009.v.002.
Pełny tekst źródłaJia, Shu. "Essence and Strategies of Grasping the Emotional Tone of the Dance". W 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.
Pełny tekst źródłaLin, Jui-An, i Chen-Chien Hsu. "Robotic Grasping Strategies Based on Classification of Orientation State of Objects". W 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW). IEEE, 2021. http://dx.doi.org/10.1109/icce-tw52618.2021.9602960.
Pełny tekst źródłaTurco, Enrico, Valerio Bo, Mehrdad Tavassoli, Maria Pozzi i Domenico Prattichizzo. "Learning Grasping Strategies for a Soft Non-Anthropomorphic Hand from Human Demonstrations". W 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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