Relevant bibliographies by topics / Kinodynamic motion planning

Academic literature on the topic 'Kinodynamic motion planning'

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Published: 14 March 2023

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Journal articles on the topic "Kinodynamic motion planning"

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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.

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Donald, 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.

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Choi, 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.

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Kulathunga, 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.

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Any obstacle-free path planning algorithm, in general, gives a sequence of waypoints that connect start and goal positions by a sequence of straight lines, which does not ensure the smoothness and the dynamic feasibility to maneuver the MAV. Kinodynamic-based motion planning is one of the ways to impose dynamic feasibility in planning. However, kinodynamic motion planning is not an optimal solution due to high computational demands for real-time applications. Thus, we explore path planning followed by kinodynamic smoothing while ensuring the dynamic feasibility of MAV. The main difference in the proposed technique is not to use kinodynamic planning when finding a feasible path, but rather to apply kinodynamic smoothing along the obtained feasible path. We have chosen a geometric-based path planning algorithm “RRT*” as the path finding algorithm. In the proposed technique, we modified the original RRT* introducing an adaptive search space and a steering function that helps to increase the consistency of the planner. Moreover, we propose a multiple RRT* that generates a set of desired paths. The optimal path from the generated paths is selected based on a cost function. Afterwards, we apply kinodynamic smoothing that will result in a dynamically feasible as well as obstacle-free path. Thereafter, a b-spline-based trajectory is generated to maneuver the vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. According to the experiment results, we were able to speed up the path planning task by 1.3 times when using the proposed multiple RRT* over the original RRT*.
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Pham, 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.

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Path-velocity decomposition is an intuitive yet powerful approach to addressing the complexity of kinodynamic motion planning. The difficult trajectory planning problem is solved in two separate, simpler steps: first, a path is found in the configuration space that satisfies the geometric constraints (path planning), and second, a time-parameterization of that path satisfying the kinodynamic constraints is found. A fundamental requirement is that the path found in the first step must be time-parameterizable. Most existing works fulfill this requirement by enforcing quasi-static constraints during the path planning step, resulting in an important loss in completeness. We propose a method that enables path-velocity decomposition to discover truly dynamic motions, i.e. motions that are not quasi-statically executable. At the heart of the proposed method is a new algorithm – Admissible Velocity Propagation – which, given a path and an interval of reachable velocities at the beginning of that path, computes exactly and efficiently the interval of all the velocities the system can reach after traversing the path, while respecting the system’s kinodynamic constraints. Combining this algorithm with usual sampling-based planners then gives rise to a family of new trajectory planners that can appropriately handle kinodynamic constraints while retaining the advantages associated with path-velocity decomposition. We demonstrate the efficiency of the proposed method on some difficult kinodynamic planning problems, where, in particular, quasi-static methods are guaranteed to fail.
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Ha, 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.

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AbstractThis paper extends the RRT* algorithm, a recently developed but widely used sampling based optimal motion planner, in order to effectively handle nonlinear kinodynamic constraints. Nonlinearity in kinodynamic differential constraints often leads to difficulties in choosing an appropriate distance metric and in computing optimized trajectory segments in tree construction. To tackle these two difficulties, this work adopts the affine quadratic regulator-based pseudo-metric as the distance measure and utilizes iterative two-point boundary value problem solvers to compute the optimized segments. The proposed extension then preserves the inherent asymptotic optimality of the RRT* framework, while efficiently handling a variety of kinodynamic constraints. Three numerical case studies validate the applicability of the proposed method.
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Ogay, 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.

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Hsu, 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.

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Sakcak, 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.

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MOTONAKA, 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.

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Dissertations / Theses on the topic "Kinodynamic motion planning"

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Boeuf, Alexandre. "Kinodynamic motion planning for quadrotor-like aerial robots." Phd thesis, Toulouse, INPT, 2017. http://oatao.univ-toulouse.fr/20169/1/Boeuf.pdf.

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Motion planning is the field of computer science that aims at developing algorithmic techniques allowing the automatic computation of trajecto- ries for a mechanical system. The nature of such a system vary according to the fields of application. In computer animation it could be a humanoid avatar. In molecular biology it could be a protein. The field of application of this work being aerial robotics, the system is here a four-rotor UAV (Unmanned Aerial Vehicle) called quadrotor. The motion planning problem consists in computing a series of motions that brings the system from a given initial configuration to a desired final configuration without generating collisions with its environment, most of the time known in advance. Usual methods explore the system’s configuration space regardless of its dynamics. By construction the thrust force that allows a quadrotor to fly is tangential to its attitude which implies that not every motion can be performed. Furthermore, the magnitude of this thrust force and hence the linear acceleration of the center of mass are limited by the physical capabilities of the robot. For all these reasons, not only position and orientation must be planned, higher derivatives must be planned also if the motion is to be executed. When this is the case we talk of kinodynamic motion planning. A distinction is made between the local planner and the global planner. The former is in charge of producing a valid trajectory between two states of the system without necessarily taking collisions into account. The later is the overall algorithmic process that is in charge of solving the motion planning problem by exploring the state space of the system. It relies on multiple calls to the local planner. We present a local planner that interpolates two states consisting of an arbitrary number of degrees of freedom (dof) and their first and second derivatives. Given a set of bounds on the dof derivatives up to the fourth order (snap), it quickly produces a near-optimal minimum time trajectory that respects those bounds. In most of modern global motion planning algorithms, the exploration is guided by a distance function (or metric). The best choice is the cost-to-go, i.e. the cost associated to the local method. In the context of kinodynamic motion planning, it is the duration of the minimal-time trajectory. The problem in this case is that computing the cost-to-go is as hard (and thus as costly) as computing the optimal trajectory itself. We present a metric that is a good approximation of the cost-to-go but which computation is far less time consuming. The dominant paradigm nowadays is sampling-based motion planning. This class of algorithms relies on random sampling of the state space in order to quickly explore it. A common strategy is uniform sampling. It however appears that, in our context, it is a rather poor choice. Indeed, a great majority of uniformly sampled states cannot be interpolated. We present an incremental sampling strategy that significantly decreases the probability of this happening.
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Bilge, 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.

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Kinodynamic motion planning is an important problem in robotics. It consists of planning the dynamic motion of a robotic system taking into account its kinematic and dynamic constraints. For this class of problems, high dimensionality is a major difficulty and finding an exact time optimal robot motion trajectory is proven to be NP-hard. Probabilistic approximate techniques have therefore been proposed in the literature to solve particular problem instances. These methods include Randomized Potential Field Planners (RPP), Probabilistic Roadmaps (PRM) and Rapidly Exploring Random Trees (RRT). When physical obstacles and differential constraints are added to the problem, applying RPPs or PRMs encounter difficulties. In order to handle these difficulties, RRTs have been proposed. In this study, we consider a multiple camera industrial inspection problem where the concurrent motion of these cameras needs to be planned. The cameras are required to capture maximum number of defect locations while globally avoiding collisions with each other and with obstacles. Our approach is to consider a solution to the kinodynamic planning problem of multiple camera inspection by making use of the RRT algorithm. We explore and resolve issues arising when RRTs are applied to this specific problem class. Along these lines, we consider the cases of a single camera without obstacles and then with obstacles. Then, we attempt to extend the study to the case of multiple camera where we also need to avoid collisions between cameras. We present simulation results to show the performance of our RRT based approach to different instrument configurations and compare with existing deterministic approaches.
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Paden, Brian. "A generalized label correcting method for optimal kinodynamic motion planning." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113505.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
Cataloged 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.
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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.

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This thesis presents a minimum energy optimal sampling-based motion planning algorithm, MEAQR RRT*, specifically for systems with non-linear dynamics, non-holonomic and actuation constraints. The motion planner developed is intended for unmanned aerial systems (UAS) whether they be fixed or rotary wing. The eventual implementation in this thesis revolves around a quadrotor platform. This work extends the algorithms presented previously by Webb et al. and Glassman et al. by formulating a fixed-final-state-free-final-time open loop state space pseudometric for nearest neighbours search and the appropriate closed loop steering method for the tree extension heuristic. By doing so, it allows the introduction of constraints on actuation magnitude and bandwidth. The controller is formulated by solving a minimization problem for the amount of input energy used to connect two states along a trajectory segment. This thesis argues that this properly tuned pseudometric integrated into a state space exploring algorithm results in a trajectory with minimal energy expenditure, which is extremely beneficial for present-day battery limited capabilities of unmanned aerial systems. The algorithm is demonstrated on two example systems (1) a simple 2D pendulum with actuation constraints and (2) a quadrotor described by a 13-dimensional state-space model. In addition, an environment modelling procedure is designed, implemented and tested for a-priori map building required in order to test the algorithm on a real life environment.
Cette 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.
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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.

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Robot actuators have physical limitations in how fast they can change their velocity. The more accurately planning algorithms consider these limitations, the better the robot is able to perform. Sampling-based algorithms have been successful in geometric domains, which ignore actuator limitations. They are simple, parameter-free, probabilistically complete and fast. Even though some algorithms like RRTs were specifically designed for kinodynamic problems, which take actuator limitations into account, they are less efficient in these domains or are, as we show, not probabilistically complete. A common approach to this problem is to decompose it, first planning a geometric path and then time-parameterizing it such that actuator constraints are satisfied. We improve the reliability of the latter step. However, the decomposition approach can neither deal with non-zero start or goal velocities nor provides an optimal solution. We demonstrate that sampling-based algorithms can be extended to consider actuator limitations in the form of acceleration limits while retaining the same advantageous properties as in geometric domains. We present an asymptotically optimal planner by combining a steering method with the RRT* algorithm. In addition, we present hierarchical rejection sampling to improve the efficiency of informed kinodynamic planning in high-dimensional spaces.
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Cowley, 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.

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Thesis (MScEng)--Stellenbosch University, 2013.
ENGLISH 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.
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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.

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La synthèse automatique du mouvement de robots à pattes est un enjeu majeur de la robotique: sa résolution permettrait le déploiement des robots hors de leurs laboratoire. Pour y parvenir, cette thèse suit l'approche "diviser pour régner", où le problème est décomposé en plusieurs sous-problèmes résolus séquentiellement. Cette décomposition amène alors la question nouvelle de la faisabilité: comment garantir que la solution d'un sous-problème, permet la résolution des suivants (dont elle sert d'entrée)? Pour y répondre, cette thèse définit des critères de faisabilités efficaces, qui s'appuient sur la définition des contraintes qui s'appliquent au centre de masse du robot. En parallèle, et de manière plus générale, elle propose une nouvelle formulation du problème du calcul d'une trajectoire valide pour le centre de masse du robot. Cette formulation, continue, présente le double avantage (par rapport aux méthodes discrètes classiques) de garantir la validité de la solution en tous points, tout en améliorant, grâce à une réduction de la dimensionnalité du problème, les performances des algorithmes de l'état de l'art. L'architecture de planification de mouvement résultante a été validée en simulation, ainsi que sur le robot HRP-2, démontrant ainsi sa supériorité en termes de temps de calcul et de taux de succès par rapport à l'existant
The 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
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Book chapters on the topic "Kinodynamic motion planning"

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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.

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Paden, 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.

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Motonaka, 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.

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This chapter describes kinodynamic motion planning and its application. Kinodynamics is the discipline that tries to solve kinematic constraints and dynamical constraints simultaneously. By using kinodynamic motion planning, control inputs can be generated in a much simpler way, compared to the conventional motion planning that solves kinematics and dynamics separately. After briefly overviewing the kinodynamic motion planning, its application to a flying robot is described in detail.
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"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.

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Motonaka, 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.

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Since a nonholonomic system such as a robot with two independent driving wheels includes complicated nonlinear terms generally, it is hard to realize a stable and tractable controller design. However, about a dynamic control method for the motion planning, it is guaranteed that a nonholonomic-controlled object can always be converged to an arbitrary point using a control method based on an invariant manifold. Based on it, the method called “kinodynamic motion planning” was proposed to converge the states of the two-wheeled mobile robot to the arbitrary target position while avoiding obstacles by combining the control based on the invariant manifold and the HPF. In this chapter, how to combine the invariant manifold control and the concept of the HPF is explained in detail, and the usefulness of the proposed approach is verified through some simulations.
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"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.

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"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.

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Conference papers on the topic "Kinodynamic motion planning"

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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.

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Matebese, 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.

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Pivtoraiko, 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.

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Pivtoraiko, 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.

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S¸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.

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This paper presents computational and experimental evidence that it is possible to plan and execute dynamic motions that involve chain reconfiguration for modular reconfigurable robots in the presence of obstacles. At the heart of the approach is the use of a sampling-based motion planner that is tightly integrated with a physics-based dynamic simulator. To evaluate the method, the planner is used to compute motions for a chain robot constructed from CKbot modules to perform a reconfiguration, attaching more modules and continuing a dynamic motion while avoiding obstacles. These motions are then executed on hardware and compared with the ones predicted by the planner.
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Motonaka, 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.

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Hart, 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.

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Palmieri, 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.

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Zhang, 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.

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Qin, 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.

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Reports on the topic "Kinodynamic motion planning"

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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.

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