Academic literature on the topic 'Poisson robotisé'
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Journal articles on the topic "Poisson robotisé":
Hasse, Alexander, and Kristian Mauser. "Poisson Induced Bending Actuator for Soft Robotic Systems." Soft Robotics 7, no. 2 (April 1, 2020): 155–67. http://dx.doi.org/10.1089/soro.2018.0163.
Schiemer, Jonas F., Karen Stumm, Karin H. Somerlik-Fuchs, Klaus-Peter Hoffmann, Jan Baumgart, and Werner Kneist. "Robotic Setup Promises Consistent Effects of Multilocular Gastrointestinal Electrical Stimulation: First Results of a Porcine Study." European Surgical Research 61, no. 1 (2020): 14–22. http://dx.doi.org/10.1159/000506799.
Refaai, Mohamad Reda A., M. N. Manjunatha, S. Radjarejesri, B. Ramesh, Ram Subbiah, and Nahom Adugna. "Nanorobots with Hybrid Biomembranes for Simultaneous Degradation of Toxic Microorganism." Advances in Materials Science and Engineering 2022 (September 23, 2022): 1–12. http://dx.doi.org/10.1155/2022/2391843.
Watson, Michael D., Sally J. Trufan, Nicole L. Gower, Joshua S. Hill, and Jonathan C. Salo. "Effect of Surgical Approach on Node Harvest in Robotic Gastrectomy." American Surgeon 85, no. 8 (August 2019): 794–99. http://dx.doi.org/10.1177/000313481908500827.
Liu, Wangyu, Zheng Liu, Zhengqiang Guo, Zhaoqi Chen, and Weigui Xie. "Application of Poisson’s ratio structures and decoupling algorithm for 3D force sensing." Measurement Science and Technology 35, no. 6 (March 12, 2024): 065105. http://dx.doi.org/10.1088/1361-6501/ad3018.
Vázquez-Arellano, Manuel, David Reiser, Dimitrios Paraforos, Miguel Garrido-Izard, and Hans Griepentrog. "Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions." Robotics 7, no. 4 (October 11, 2018): 63. http://dx.doi.org/10.3390/robotics7040063.
Kazerooni, H., Mark S. Evans, and J. Jones. "Hydrostatic Force Sensor for Robotic Applications." Journal of Dynamic Systems, Measurement, and Control 119, no. 1 (March 1, 1997): 115–19. http://dx.doi.org/10.1115/1.2801201.
Serpen, Gursel, and Jayanta Debnath. "Design and performance evaluation of a parking management system for automated, multi-story and robotic parking structure." International Journal of Intelligent Computing and Cybernetics 12, no. 4 (November 11, 2019): 444–65. http://dx.doi.org/10.1108/ijicc-02-2019-0017.
Li, Yue, Stelian Coros, and Bernhard Thomaszewski. "Neural Metamaterial Networks for Nonlinear Material Design." ACM Transactions on Graphics 42, no. 6 (December 5, 2023): 1–13. http://dx.doi.org/10.1145/3618325.
Duits, Remco, Erik J. Bekkers, and Alexey Mashtakov. "Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs." Entropy 21, no. 1 (January 8, 2019): 38. http://dx.doi.org/10.3390/e21010038.
Dissertations / Theses on the topic "Poisson robotisé":
Israilov, Sardor. "De l'identification basée apprentissage profond à la commande basée modèle." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4003.
Fish swimming remains a complex subject that is not yet fully understood due to the inter-section of biology and fluid dynamics. Through years of evolution, organisms in nature have perfected their biological mechanisms to navigate efficiently in their environment and adaptto particular situations. Throughout history, mankind has been inspired by nature to innovateand develop nature-like systems. Biomimetic robotic fish, in particular, has a number of appli-cations in the real world and its control is yet to be optimized. Deep Reinforcement Learning showed excellent results in control of robotic systems, where dynamics is too complex to befully modeled and analyzed. In this thesis, we explored new venues of control of a biomimetic fish via reinforcement learning to effectively maximize the thrust and speed. However, to fully comprehend the newly-emerged data-based algorithms, we first studied the application of these methods on a standard benchmark of a control theory, the inverted pendulum with a cart. We demonstrated that deep Reinforcement Learning could control the system without any prior knowledge of the system, achieving performance comparable to traditional model-based con-trol theory methods. In the third chapter, we focus on the undulatory swimming of a roboticfish, exploring various objectives and information sources for control. Our studies indicate that the thrust force of a robotic fish can be optimized using inputs from both force sensors and cameras as feedback for control. Our findings demonstrate that a square wave control with a particular frequency maximizes the thrust and we rationalize it using Pontryagin Maximum Principle. An appropriate model is established that shows an excellent agreement between simulation and experimental results. Subsequently, we concentrate on the speed maximization of a robotic fish both in several virtual environments and experiments using visual data. Once again, we find that deep Reinforcement Learning can find an excellent swimming gait with a square wave control that maximizes the swimming speed
Tapia, Siles Silvia Cecilia. "Robotic locomotion in turbulent flow." Paris 6, 2011. http://www.theses.fr/2011PA066414.
Chemtob, Yohann. "Collective behaviour of zibrafish and robot groups in a constrained environment." Thesis, Université de Paris (2019-....), 2020. http://www.theses.fr/2020UNIP7017.
Collective movement can be observed throughout the animal kingdom, particularly in fish. Yet, despite many studies on the subject, the decision-making mechanisms of these collective events remain poorly understood.In this thesis, we want to better understand collective movement by studying more precisely the decision-making process, the organisation and the cohesion of groups of social fish. Our study focuses on the zebrafish (Danio rerio), a model used in different areas of research. To highlight those behaviours, we have developed a specific constrained environment composed of two rooms connected by a corridor. Cohesion on groups of different sizes and the organisation of leadership have been examined. The collective behaviour of zebrafish in a constrained environment was then described throughout a multi-contextual stochastic model. We have also developed a robotic agent to determine the importance of aspect and behaviour in conspecific recognition. Finally, after its integration into the group, we influenced the movements of the fish group with this biomimetic and autonomous fish robot to test our hypotheses on the different rules underlying collective movements.We have achieved the following results. In a constrained environment, fish use the rooms as resting areas and frequently move from one area to another. We observed that the size of fish groups influences the structure and proportion of these transitions. Group size also changes the cohesion between individuals and their spatial distribution. We studied more precisely the decision-making process during transitions, and in particular the mechanics of leadership. We have shown that leadership is shared among all individuals in a group, with heterogeneous sharing modalities between the different groups studied. The stochastic model developed from these results correctly simulates fish group behaviour in a constrained environment, using different parameter values according to the position of the agent. We have succeeded in integrating an autonomous and biomimetic fish robot into a group of zebrafish. The use of the stochastic model to drive the robot has highlighted the importance of biomimetic behaviour in the process of recognising a conspecific. Finally, we modulated the behaviour of the zebrafish with the fish robot by inducing collective departures as well as significantly biasing the distribution of fish between the two rooms. These positive results allow us to validate the hypotheses about leadership and cohesion among social fish
Porez, Mathieu. "Modèle dynamique analytique de la nage tridimensionnelle anguilliforme pour la robotique." Phd thesis, Nantes, 2007. https://archive.bu.univ-nantes.fr/pollux/show/show?id=b35b23ba-3371-4f6b-9b34-d4e9b084b999.
The presented work in this thesis is devoted to the development of a dynamic model for the anguilliform swim suited to the real time control of the future biomimetic "Eel-like robot" of the ROBEA-CNRS project of the same name. The computation of the interactions between a deformable body and the fluid, in which it moves, is a complex problem requiring the integration of the Navier-Stokes equations and the non-linear dynamic equations of the body enduring finished transformations. Pursuing goals of control for robotic, the suggested solution is based on the fusion of two theories: the Slender Body Theory of the fluid mechanic and Cosserat Beam Theory of the solid mechanic. The first theory models the 3-D flow around fish by the stratification "slices by slices" of the bidimensional flows and transverse with the principal axis of the animal's body. Basing on the second theory, the fish is modeled by a continuous assembly of rigid sections that represents the animal's vertebrae or the eel-like robot's rigid platforms. On the basis of this model,the purpose of the presented work is to establish the dynamics of the head and the vertebrae of fish in order to work out a numerical algorithm based on the "Newton-Euler formalism". Finally, the obtained simulator works in real time with a good level of precision (i. E. Lower than 10\%) compared with the numerical computations of the Navier-Stokes equations
Porez, Mathieu. "Modèle dynamique analytique de la nage tridimensionnelle anguilliforme pour la robotique." Phd thesis, Université de Nantes, 2007. http://tel.archives-ouvertes.fr/tel-00630940.
Matar, Younes. "Etude expérimentale de la nage anguilliforme : application à un robot biomimétique." Phd thesis, Ecole des Mines de Nantes, 2013. http://tel.archives-ouvertes.fr/tel-00821185.
Books on the topic "Poisson robotisé":
STAMPER, JUDITH BAUER. BT-DECEPTICON POISON#6 (Transformers, No 6). Ballantine Books, 1986.
Book chapters on the topic "Poisson robotisé":
Pahlajani, Chetan D., Indrajeet Yadav, Herbert G. Tanner, and Ioannis Poulakakis. "Decision-Making Accuracy for Sensor Networks with Inhomogeneous Poisson Observations." In Distributed Autonomous Robotic Systems, 177–90. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73008-0_13.
Nasiri, Simin. "Auxetic Grammars: An Application of Shape Grammar Using Shape Machine to Generate Auxetic Metamaterial Geometries for Fabricating Sustainable Kinetic Panels." In Computational Design and Robotic Fabrication, 114–24. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8405-3_10.
Chen, Tony G., Billie C. Goolsby, Guadalupe Bernal, Lauren A. O’Connell, and Mark R. Cutkosky. "Feed Me: Robotic Infiltration of Poison Frog Families." In Biomimetic and Biohybrid Systems, 293–302. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39504-8_20.
Ramachandra, Krishna, Catherine Jiayi Cai, Seenivasan Lalithkumar, Xinchen Cai, Zion Tszho Tse, and Hongliang Ren. "Tunable stiffness using negative Poisson's ratio toward load-bearing continuum tubular mechanisms in medical robotics." In Control Theory in Biomedical Engineering, 317–58. Elsevier, 2020. http://dx.doi.org/10.1016/b978-0-12-821350-6.00012-3.
Conference papers on the topic "Poisson robotisé":
Park, Chonhyon, Jia Pan, and Dinesh Manocha. "Poisson-RRT." In 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014. http://dx.doi.org/10.1109/icra.2014.6907541.
Al-Allaq, Aiman, Nebojsa Jaksic, Bahaa Ansaf, Jude DePalma, and Trung Duong. "Modified Nernst-Plank-Poisson Model for IPMC With Back-Relaxation Effects." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10084.
Vizzo, Ignacio, Xieyuanli Chen, Nived Chebrolu, Jens Behley, and Cyrill Stachniss. "Poisson Surface Reconstruction for LiDAR Odometry and Mapping." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9562069.
Hess, Jurgen, Maximilian Beinhofer, Daniel Kuhner, Philipp Ruchti, and Wolfram Burgard. "Poisson-driven dirt maps for efficient robot cleaning." In 2013 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2013. http://dx.doi.org/10.1109/icra.2013.6630880.
Barabash, Oleg, Andrii Musienko, Andriy Makarchuk, Salanda Ivanna, Dmytro Obidin, and Oleg Ilin. "Abel-Poisson Partial Sums in Signal Theory." In 2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2024. http://dx.doi.org/10.1109/hora61326.2024.10550475.
Petrouš, Matej, Evženie Suzdaleva, and Ivan Nagy. "Modeling of Passenger Demand using Mixture of Poisson Components." In 16th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007831306170624.
Uglickich, Evženie, Ivan Nagy, and Matej Petrouš. "Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data." In 18th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010575006000608.
Uglickich, Evženie, Ivan Nagy, and Matej Petrouš. "Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data." In 18th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010575000002994.
Choudhury, Sanjiban, Sebastian Scherer, and Andrew Bagnell. "Theoretical Limits of Speed and Resolution for Kinodynamic Planning in a Poisson Forest." In Robotics: Science and Systems 2015. Robotics: Science and Systems Foundation, 2015. http://dx.doi.org/10.15607/rss.2015.xi.005.
Qian, Huimin, Jun Zhou, Xinbiao Lu, and Xinye Wu. "Human activities recognition based on poisson equation evaluation and bidirectional 2DPCA." In 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2014. http://dx.doi.org/10.1109/icarcv.2014.7064404.