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Статті в журналах з теми "Kinodynamic motion planning"
Masoud, Ahmad. "Kinodynamic Motion Planning." IEEE Robotics & Automation Magazine 17, no. 1 (March 2010): 85–99. http://dx.doi.org/10.1109/mra.2010.935794.
Повний текст джерелаDonald, Bruce, Patrick Xavier, John Canny, and John Reif. "Kinodynamic motion planning." Journal of the ACM 40, no. 5 (November 1993): 1048–66. http://dx.doi.org/10.1145/174147.174150.
Повний текст джерелаChoi, Jiwung. "Kinodynamic Motion Planning for Autonomous Vehicles." International Journal of Advanced Robotic Systems 11, no. 6 (January 2014): 90. http://dx.doi.org/10.5772/58683.
Повний текст джерелаKulathunga, G., D. Devitt, R. Fedorenko, and A. Klimchik. "Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)." Nelineinaya Dinamika 17, no. 4 (2021): 491–505. http://dx.doi.org/10.20537/nd210410.
Повний текст джерелаPham, Quang-Cuong, Stéphane Caron, Puttichai Lertkultanon, and Yoshihiko Nakamura. "Admissible velocity propagation: Beyond quasi-static path planning for high-dimensional robots." International Journal of Robotics Research 36, no. 1 (November 2, 2016): 44–67. http://dx.doi.org/10.1177/0278364916675419.
Повний текст джерелаHa, Jung-Su, Han-Lim Choi, and Jeong Hwan Jeon. "Iterative methods for efficient sampling-based optimal motion planning of nonlinear systems." International Journal of Applied Mathematics and Computer Science 28, no. 1 (March 1, 2018): 155–68. http://dx.doi.org/10.2478/amcs-2018-0012.
Повний текст джерелаOgay, Dmitriy, and Eun-Gyung Kim. "Kinodynamic Motion Planning with Artificial Wavefront Propagation." Journal of information and communication convergence engineering 11, no. 4 (December 31, 2013): 274–81. http://dx.doi.org/10.6109/jicce.2013.11.4.274.
Повний текст джерелаHsu, David, Robert Kindel, Jean-Claude Latombe, and Stephen Rock. "Randomized Kinodynamic Motion Planning with Moving Obstacles." International Journal of Robotics Research 21, no. 3 (March 2002): 233–55. http://dx.doi.org/10.1177/027836402320556421.
Повний текст джерелаSakcak, Basak, Luca Bascetta, Gianni Ferretti, and Maria Prandini. "Sampling-based optimal kinodynamic planning with motion primitives." Autonomous Robots 43, no. 7 (January 14, 2019): 1715–32. http://dx.doi.org/10.1007/s10514-019-09830-x.
Повний текст джерелаMOTONAKA, Kimiko, Keigo WATANABE, and Shoichi MAEYAMA. "Kinodynamic motion planning and control for a quadrotor." Transactions of the JSME (in Japanese) 81, no. 825 (2015): 14–00631. http://dx.doi.org/10.1299/transjsme.14-00631.
Повний текст джерелаДисертації з теми "Kinodynamic motion planning"
Boeuf, Alexandre. "Kinodynamic motion planning for quadrotor-like aerial robots." Phd thesis, Toulouse, INPT, 2017. http://oatao.univ-toulouse.fr/20169/1/Boeuf.pdf.
Повний текст джерелаBilge, Burak. "Rrt Based Kinodynamic Motion Planning For Multiple Camera Industrial Inspection." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610543/index.pdf.
Повний текст джерелаPaden, Brian. "A generalized label correcting method for optimal kinodynamic motion planning." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113505.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references and index.
Nearly all autonomous robotic systems use some form of motion planning to compute reference motions through their environment. An increasing use of autonomous robots in a broad range of applications creates a need for efficient, general purpose motion planning algorithms that are applicable in any of these new application domains. This thesis presents a resolution complete optimal kinodynamic motion planning algorithm based on a direct forward search of the set of admissible input signals to a dynamical model. The advantage of this generalized label correcting method is that it does not require a local planning subroutine as in the case of related methods. Preliminary material focuses on new topological properties of the canonical problem formulation that are used to show continuity of the performance objective. These observations are used to derive a generalization of Bellman's principle of optimality in the context of kinodynamic motion planning. A generalized label correcting algorithm is then proposed which leverages these results to prune candidate input signals from the search when their cost is greater than related signals. The second part of this thesis addresses admissible heuristics for kinodynamic motion planning. An admissibility condition is derived that can be used to verify the admissibility of candidate heuristics for a particular problem. This condition also characterizes a convex set of admissible heuristics. A linear program is formulated to obtain a heuristic which is as close to the optimal cost-to-go as possible while remaining admissible. This optimization is justified by showing its solution coincides with the solution to the Hamilton-Jacobi-Bellman equation. Lastly, a sum-of-squares relaxation of this infinite-dimensional linear program is proposed for obtaining provably admissible approximate solutions.
by Brian A. Paden.
Ph. D.
Rikovitch, Nir. "Kinodynamic non-holonomic motion planning for UAVs: a minimum energy approach." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121538.
Повний текст джерелаCette thèse présente un algorithme de planification de mouvement qui minimise l'utilisation d'énergie utilisant une approche d'échantillonnage. Cette algorithme est nommé MEAQR RRT*, il a été conçue pour les systèmes non-linéaire dynamiques, non-holonomique et avec contraintes d'actionnements. Ce planificateur de mouvement a été développé pour les systèmes aériens sans pilotes (UAS) soit avec ailes fixes ou rotationnelles. Ce mémoire pourrait éventuellement planifier des chemins pour une plateforme quadrotor. Ce travail est un extension des algorithmes présenté Webb et al. et Glassman et al. en formulant un état fixe final et libre dans un espace d'états ouverts afin de trouver le voisin le plus prés et la méthode appropriée pour fermé les boucles de conduite. Ceci permet d'introduire des contraintes d'actionnements sur la grandeur et l'intensité. Ce contrôleur résout le problème de minimiser l'énergie utilisé afin de connecter deux états selon une trajectoire. Il est discuté que ce pseudo-métrique intégré a l'exploration d'états résulte en une trajectoire qui minimise l'utilisation d'énergie. Ceci permet de réduire la consommation d'énergie sur les batteries aux capacités limités d'UAS. Il est démontré la puissance de notre système par l'entremise de deux exemples, un simple pendule avec des contraintes d'activation en deux dimensions et en modélisant un quadrotor avec un espace d'état a 13 dimensions. De plus, une procédure de conceptualisation a été conçu, implémenté et testé afin d'évaluer les besoins d'un plan afin de tester le modèle présenté dans un environnement réel.
Kunz, Tobias. "Time-optimal sampling-based motion planning for manipulators with acceleration limits." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53569.
Повний текст джерелаCowley, Edwe Gerrit. "Kinodynamic planning for a fixed-wing aircraft in dynamic, cluttered environments : a local planning method using implicitly-defined motion primitives." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80077.
Повний текст джерелаENGLISH ABSTRACT: In order to navigate dynamic, cluttered environments safely, fully autonomous Unmanned Aerial Vehicles (UAVs) are required to plan conflict-free trajectories between two states in position-time space efficiently and reliably. Kinodynamic planning for vehicles with non-holonomic dynamic constraints is an NP-hard problem which is usually addressed using sampling-based, probabilistically complete motion planning algorithms. These algorithms are often applied in conjunction with a finite set of simple geometric motion primitives which encapsulate the dynamic constraints of the vehicle. This ensures that composite trajectories generated by the planning algorithm adhere to the vehicle dynamics. For many vehicles, accurate tracking of position-based trajectories is a non-trivial problem which demands complicated control techniques with high energy requirements. In an effort to reduce control complexity and thus also energy consumption, a generic Local Planning Method (LPM), able to plan trajectories based on implicitly-defined motion primitives, is developed in this project. This allows the planning algorithm to construct trajectories which are based on simulated results of vehicle motion under the control of a rudimentary auto-pilot, as opposed to a more complicated position-tracking system. The LPM abstracts motion primitives in such a way that it may theoretically be made applicable to various vehicles and control systems through simple substitution of the motion primitive set. The LPM, which is based on a variation of the Levenberg-Marquardt Algorithm (LMA), is integrated into a well-known Probabilistic Roadmap (PRM) kinodynamic planning algorithm which is known to work well in dynamic and cluttered environments. The complete motion planning algorithm is tested thoroughly in various simulated environments, using a vehicle model and controllers which have been previously verified against a real UAV during practical flight tests.
AFRIKAANSE OPSOMMING: Ten einde dinamiese, voorwerpryke omgewings veilig te navigeer, word daar vereis dat volledig-outonome onbemande lugvoertuie konflikvrye trajekte tussen twee posisie-tydtoestande doeltreffend en betroubaar kan beplan. Kinodinamiese beplanning is ’n NPmoeilike probleem wat gewoonlik deur middel van probabilisties-volledige beplanningsalgoritmes aangespreek word . Hierdie algoritmes word dikwels in kombinasie met ’n eindige stel eenvoudige geometriese maneuvers, wat die dinamiese beperkings van die voertuig omvat, ingespan. Sodanig word daar verseker dat trajekte wat deur die beplaningsalgoritme saamgestel is aan die dinamiese beperkings van die voertuig voldoen. Vir baie voertuie, is die akkurate volging van posisie-gebaseerde trajekte ’n nie-triviale probleem wat die gebruik van ingewikkelde, energie-intensiewe beheertegnieke vereis. In ’n poging om beheer-kompleksiteit, en dus energie-verbruik, te verminder, word ’n generiese plaaslike-beplanner voorgestel. Hierdie algoritme stel die groter kinodinamiese beplanner in staat daartoe om trajekte saam te stel wat op empiriese waarnemings van voertuig-trajekte gebaseer is. ’n Eenvoudige beheerstelsel kan dus gebruik word, in teenstelling met die meer ingewikkelde padvolgingsbeheerders wat benodig word om eenvoudige geometriese trajekte akkuraat te volg. Die plaaslike-beplanner abstraeer maneuvers in so ’n mate dat dit teoreties op verskeie voertuie en beheerstelsels van toepassing gemaak kan word deur eenvoudig die maneuver-stel te vervang. Die plaaslike-beplanner, wat afgelei is van die Levenberg-Marquardt-Algoritme (LMA), word in ’n welbekende “Probabilistic Roadmap” (PRM) kinodinamiese-beplanningsalgoritme geïntegreer. Dit word algemeen aanvaar dat die PRM effektief werk in dinamiese, voorwerpryke omgewings. Die volledige beplanningsalgoritme word deeglik in verskeie, gesimuleerde omgewings getoets op ’n voertuig-model en -beheerders wat voorheen vir akkuraatheid teenoor ’n werklike voertuig gekontroleer is tydens praktiese vlugtoetse.
Fernbach, Pierre. "Modèles réduits fiables et efficaces pour la planification et l'optimisation de mouvement des robots à pattes en environnements contraints." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30232.
Повний текст джерелаThe automatic synthesis of movements for legged robots is one of the long standing challenge of robotics, and its resolution is a prior to the safe deployment of robots outside of their labs. In this thesis, we tackle it with a divide and conquer approach, where several smaller sub-problems are identified and solved sequentially to generate motions in a computationally efficient manner. This decoupling comes with a feasibility issue : how can we guarantee that the solution of a sub-problem is a valid input for the next sub-problem ? To address this issue, this thesis defines computationally efficient feasibility criteria, focused on the constraints on the Center Of Mass of the robot. Simultaneously, it proposes a new formulation of the problem of computing a feasible trajectory for the Center Of Mass of the robot, given a contact sequence. This formulation is continuous, as opposed to traditional approaches that rely on a discretized formulation, which can result in constraint violations and are less computationally efficient. This general formulation could be straightforwardly used with any existing approach of the state of the art. The framework obtained was experimentally validated both in simulation and on the HRP-2 robot, and presented a higher success rate, as well as computing performances order of magnitudes faster than the state of the art
Частини книг з теми "Kinodynamic motion planning"
Şucan, Ioan A., and Lydia E. Kavraki. "Kinodynamic Motion Planning by Interior-Exterior Cell Exploration." In Springer Tracts in Advanced Robotics, 449–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00312-7_28.
Повний текст джерелаPaden, Brian, and Emilio Frazzoli. "A Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning." In Springer Proceedings in Advanced Robotics, 512–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43089-4_33.
Повний текст джерелаMotonaka, Kimiko, Keigo Watanabe, and Shoichi Maeyama. "Kinodynamic Motion Planning for an X4-Flyer." In Advances in Computational Intelligence and Robotics, 455–74. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7387-8.ch015.
Повний текст джерела"Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning." In Robotics. The MIT Press, 2008. http://dx.doi.org/10.7551/mitpress/7830.003.0040.
Повний текст джерелаMotonaka, Kimiko. "Kinodynamic Motion Planning for a Two-Wheel-Drive Mobile Robot." In Handbook of Research on Biomimetics and Biomedical Robotics, 332–46. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2993-4.ch014.
Повний текст джерела"Non-Uniform Discretization Approximations for Kinodynamic Motion Planning and its Applications." In Algorithms for Robotic Motion and Manipulation, 109–22. A K Peters/CRC Press, 1997. http://dx.doi.org/10.1201/9781439864524-13.
Повний текст джерела"Optimal Kinodynamic Motion Planning for 2D Reconfiguration of Self-Reconfigurable Robots." In Robotics. The MIT Press, 2008. http://dx.doi.org/10.7551/mitpress/7830.003.0021.
Повний текст джерелаТези доповідей конференцій з теми "Kinodynamic motion planning"
Sucan, I. A., J. F. Kruse, M. Yim, and L. E. Kavraki. "Kinodynamic motion planning with hardware demonstrations." In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2008. http://dx.doi.org/10.1109/iros.2008.4650914.
Повний текст джерелаMatebese, Belinda, Daniel Withey, and Mapundi K. Banda. "Leapfrog and optimal kinodynamic motion planning." In ICONIC: 2020 International Conference on Intelligent and Innovative Computing Applications. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3415088.3415122.
Повний текст джерелаPivtoraiko, M., and A. Kelly. "Kinodynamic motion planning with state lattice motion primitives." In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011). IEEE, 2011. http://dx.doi.org/10.1109/iros.2011.6048568.
Повний текст джерелаPivtoraiko, Mihail, and Alonzo Kelly. "Kinodynamic motion planning with state lattice motion primitives." In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011). IEEE, 2011. http://dx.doi.org/10.1109/iros.2011.6094900.
Повний текст джерелаS¸ucan, Ioan A., Jonathan F. Kruse, Mark Yim, and Lydia E. Kavraki. "Reconfiguration for Modular Robots Using Kinodynamic Motion Planning." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2296.
Повний текст джерелаMotonaka, Kimiko, Keigo Watanabe, and Shoichi Maeyama. "Motion planning of a UAV using a kinodynamic motion planning method." In IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2013. http://dx.doi.org/10.1109/iecon.2013.6700186.
Повний текст джерелаHart, Patrick, and Alois Knoll. "Kinodynamic Motion Planning Using Multi-Objective Optimization." In 2018 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2018. http://dx.doi.org/10.1109/ivs.2018.8500363.
Повний текст джерелаPalmieri, Luigi, Tomasz P. Kucner, Martin Magnusson, Achim J. Lilienthal, and Kai O. Arras. "Kinodynamic motion planning on Gaussian mixture fields." In 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017. http://dx.doi.org/10.1109/icra.2017.7989731.
Повний текст джерелаZhang, Jun. "Kinodynamic Motion Planning for Robotics: A Review." In 2021 5th International Conference on Robotics and Automation Sciences (ICRAS). IEEE, 2021. http://dx.doi.org/10.1109/icras52289.2021.9476660.
Повний текст джерелаQin, Xiangxiang, Jialun Liu, Zhengguo Liu, Shijie Li, and Chenghao Han. "Kinodynamic Motion Planning for Autonomous Surface Ships Using Motion Primitives." In 2021 6th International Conference on Transportation Information and Safety (ICTIS). IEEE, 2021. http://dx.doi.org/10.1109/ictis54573.2021.9798493.
Повний текст джерелаЗвіти організацій з теми "Kinodynamic motion planning"
Boardman, Beth, Troy Harden, and Sonia Martinez. Optimal Kinodynamic Motion Planning in Environments with Unexpected Obstacles. Office of Scientific and Technical Information (OSTI), July 2014. http://dx.doi.org/10.2172/1143991.
Повний текст джерела