Bibliografie tematiche / Tracking trajectory

Letteratura scientifica selezionata sul tema "Tracking trajectory"

Autore: Grafiati

Pubblicato: 8 giugno 2024

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Articoli di riviste sul tema "Tracking trajectory":

Howard, Srimant. "Multiple Trajectory Tracking". Scholarpedia 7, n. 4 (2012): 11287. http://dx.doi.org/10.4249/scholarpedia.11287.

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Han, Mei, Wei Xu, Hai Tao e Yihong Gong. "Multi-object trajectory tracking". Machine Vision and Applications 18, n. 3-4 (31 marzo 2007): 221–32. http://dx.doi.org/10.1007/s00138-007-0071-5.

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Gu, Jinheng, Shicheng He, Jianbo Dai, Dong Wei, Haifeng Yan, Chao Tan, Zhongbin Wang e Lei Si. "A Walking Trajectory Tracking Control Based on Uncertainties Estimation for a Drilling Robot for Rockburst Prevention". Machines 12, n. 5 (28 aprile 2024): 298. http://dx.doi.org/10.3390/machines12050298.

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Abstract (sommario):

A walking trajectory tracking control approach for a walking electrohydraulic control system is developed to reduce the walking trajectory tracking deviation and enhance robustness. The model uncertainties are estimated by a designed state observer. A saturation function is used to attenuate sliding mode chattering in the designed sliding mode controller. Additionally, a walking trajectory tracking control strategy is proposed to improve the walking trajectory tracking performance in terms of response time, tracking precision, and robustness, including walking longitudinal and lateral trajectory tracking controllers. Finally, simulation and experimental results are employed to verify the trajectory tracking performance and observability of the model uncertainties. The results testify that the proposed approach is better than other comparative methods, and the longitudinal and lateral trajectory tracking average absolute errors are controlled in 10.23 mm and 22.34 mm, respectively, thereby improving the walking trajectory tracking performance of the walking electrohydraulic control system for the coal mine drilling robot for rockburst prevention.

Vitalii, Berdyshev. "OBSERVER’S TRAJECTORY TRACKING OBJECT BYPASSING OBSTACLE ON THE SHORTEST CURVE". Eurasian Journal of Mathematical and Computer Applications 9, n. 4 (dicembre 2021): 4–16. http://dx.doi.org/10.32523/2306-6172-2021-9-4-4-16.

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Motion of some object is considered. The object t moves from the initial point t∗ to the final one t ∗ . But since absent of the direct path, he should bypass an obstacle a connected bodily set G. It is supposed that t moves by the most short trajectory T = Tt , and the trajectory T is a convex curve. The observer’s f task is to find the trajectory Tf that provides tracking the object on the most part of the object’s motion and, if possible, the lesser object’s stealth of motion along the trajectory T . The latency is defined by the distance that the observer must pass to see the object in the field of vision. The object and observer start at the same initial instant, and their velocities are equal. In the paper, examples of the trajectories Tf in R 2 are presented, on which the observer can see the object’s trajectory T ; also, the value of the object’s latency is shown for the invisible parts of the trajectory T . The variant of Tf in R 3 is shown.

Rozumnyi, Denys, Jan Kotera, Filip Šroubek e Jiří Matas. "Tracking by Deblatting". International Journal of Computer Vision 129, n. 9 (22 giugno 2021): 2583–604. http://dx.doi.org/10.1007/s11263-021-01480-w.

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AbstractObjects moving at high speed along complex trajectories often appear in videos, especially videos of sports. Such objects travel a considerable distance during exposure time of a single frame, and therefore, their position in the frame is not well defined. They appear as semi-transparent streaks due to the motion blur and cannot be reliably tracked by general trackers. We propose a novel approach called Tracking by Deblatting based on the observation that motion blur is directly related to the intra-frame trajectory of an object. Blur is estimated by solving two intertwined inverse problems, blind deblurring and image matting, which we call deblatting. By postprocessing, non-causal Tracking by Deblatting estimates continuous, complete, and accurate object trajectories for the whole sequence. Tracked objects are precisely localized with higher temporal resolution than by conventional trackers. Energy minimization by dynamic programming is used to detect abrupt changes of motion, called bounces. High-order polynomials are then fitted to smooth trajectory segments between bounces. The output is a continuous trajectory function that assigns location for every real-valued time stamp from zero to the number of frames. The proposed algorithm was evaluated on a newly created dataset of videos from a high-speed camera using a novel Trajectory-IoU metric that generalizes the traditional Intersection over Union and measures the accuracy of the intra-frame trajectory. The proposed method outperforms the baselines both in recall and trajectory accuracy. Additionally, we show that from the trajectory function precise physical calculations are possible, such as radius, gravity, and sub-frame object velocity. Velocity estimation is compared to the high-speed camera measurements and radars. Results show high performance of the proposed method in terms of Trajectory-IoU, recall, and velocity estimation.

Hu, Zhen, Daqi Zhu, Caicha Cui e Bing Sun. "Trajectory Tracking and Re-planning with Model Predictive Control of Autonomous Underwater Vehicles". Journal of Navigation 72, n. 2 (21 settembre 2018): 321–41. http://dx.doi.org/10.1017/s0373463318000668.

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The trajectory tracking of Autonomous Underwater Vehicles (AUV) is an important research topic. However, in the traditional research into AUV trajectory tracking control, the AUV often follows human-set trajectories without obstacles, and trajectory planning and tracking are separated. Focusing on this separation, a trajectory re-planning controller based on Model Predictive Control (MPC) is designed and added into the trajectory tracking controller to form a new control system. Firstly, an obstacle avoidance function is set up for the design of an MPC trajectory re-planning controller, so that the re-planned trajectory produced by the re-planning controller can avoid obstacles. Then, the tracking controller in the MPC receives the re-planned trajectory and obtains the optimal tracking control law after calculating the object function with a Sequential Quadratic Programming (SQP) optimisation algorithm. Lastly, in a backstepping algorithm, the speed jump can be sharp while the MPC tracking controller can solve the speed jump problem. Simulation results of different obstacles and trajectories demonstrate the efficiency of the proposed MPC trajectory re-planning tracking control algorithm for AUVs.

Yang, Can, e Jie Liu. "Trajectory Tracking Control of Intelligent Driving Vehicles Based on MPC and Fuzzy PID". Mathematical Problems in Engineering 2023 (3 febbraio 2023): 1–24. http://dx.doi.org/10.1155/2023/2464254.

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To improve the stability and accuracy of quintic polynomial trajectory tracking, an MPC (model predictive control) and fuzzy PID (proportional-integral-difference)- based control method are proposed. A lateral tracking controller is designed by using MPC with rule-based horizon parameters. The lateral tracking controller controls the steering angle to reduce the lateral tracking errors. A longitudinal tracking controller is designed by using a fuzzy PID. The longitudinal controller controls the motor torque and brake pressure referring to a throttle/brake calibration table to reduce the longitudinal tracking errors. By combining the two controllers, we achieve satisfactory trajectory tracking control. Relative vehicle trajectory tracking simulation is carried out under common scenarios of quintic polynomial trajectory in the Simulink/Carsim platform. The result shows that the strategy can avoid excessive trajectory tracking errors which ensures a better performance for trajectory tracking with high safety, stability, and adaptability.

Mullier, Olivier, e Julien Alexandre dit Sandretto. "Validated Trajectory Tracking using Flatness". Acta Cybernetica 25, n. 1 (3 febbraio 2021): 85–99. http://dx.doi.org/10.14232/actacyb.285729.

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The problem of a safe trajectory tracking is addressed in this paper. It consists in using the results of a validated path planner providing a set of safe trajectories to produce the set of controls to apply to remain inside this set of planned trajectories while avoiding static obstacles. This computation is performed using the differential flatness of many dynamical systems. The method is illustrated in the case of the Dubins car.

Lange, Ralph, Frank Dürr e Kurt Rothermel. "Efficient real-time trajectory tracking". VLDB Journal 20, n. 5 (12 giugno 2011): 671–94. http://dx.doi.org/10.1007/s00778-011-0237-7.

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Qu, Li Ping, Yong Yin Qu e Hao Han Zhou. "Study on Iterative Learning Control of Mobile Robot". Applied Mechanics and Materials 775 (luglio 2015): 319–23. http://dx.doi.org/10.4028/www.scientific.net/amm.775.319.

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In order to solve the mobile robot trajectory tracking problem better, an iterative learning control (ILC) was applied. And the efficiency of mobile robot trajectory tracking was improved. From the simulation result, ILC with forgetting factor has very good performance for solving mobile robot trajectory tracking problem, and the smooth of trajectory tracking process also improved well.

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Tesi sul tema "Tracking trajectory":

Bereza-Jarocinski, Robert, e Therese Persson. "Autonomous Trajectory Tracking and Obstacle Avoidance". Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214704.

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Autonomous ground vehicles (AGVs), such as selfdrivingcars, are expected to become a central part of infrastructurein future smart cities. There are many technicalchallenges with making vehicles autonomous. They have to beable to find their way in both free environments as well asin environments with obstacles and other vehicles. To achievethis, they require many sensors to analyze their surroundings.The aim with this paper is to investigate the sensor typesnormally used in AGVs, describe their functionality and alsoprovide a model of how an autonomous vehicle can navigate indifferent environments, and verify this model through simulation.Lidar, Radar, accelerometers, gyroscopes, positioning systems andcameras are the sensors that are listed. It is described whatthey measure and what this data can be used for. To model theautonomous vehicle, a car-like vehicle model is used. A trajectorytracking controller is proposed, together with a proof of itsstability using Lyapunov functions. A way to avoid stationaryobstacles using potential fields is also described. Both the trackingcontroller and the obstacle avoidance controller are shown towork as expected through simulation. The used model only allowsfor the vehicle to travel in directions within a span of ±45 of itsforward direction. Lastly, a new application for AGVs in smartcities is also proposed.

Holgersson, Anton, e Johan Gustafsson. "Trajectory Tracking for Automated Guided Vehicle". Thesis, Linköpings universitet, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176423.

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The purpose of this thesis is to investigate different control strategies on a differential drive vehicle. The vehicle should be able to drive in turns at high speed and slowly when it should park next to a charger. In both these cases, good precision in both orientation and distance to the path is important. A PID and an LQ controller have been implemented for this purpose. The two controllers were first implemented in a simulation environment. After implementing the controllers on the system itself, tests to evaluate the controllers were made to imitate real-life situations. This includes tests regarding driving with different speeds in different turns, tests with load distributions, and tests with stopping accuracy. The existing controller on the system was also tested and compared to the new controllers. After evaluating the controllers, it was stated that the existing controller was the most robust. It was not affected much by the load distribution compared to the new controllers. However, the LQ controller was slightly better in most cases, even though it was highly affected by the load distribution. The PID controller performed best regarding stopping accuracy but was the least robust controller by the three. Since the existing controller has a similar performance as the LQ controller but is more robust, the existing controller was chosen as the best one.

Bereza, Robert, e Therese Persson. "Autonomous Trajectory Tracking and Obstacle Avoidance". Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214704.

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Jamieson, Jonathan. "Trajectory generation and tracking for drone racing". Thesis, University of Strathclyde, 2018. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=29520.

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In this thesis trajectory generation for quadrotors, a type of rotorcraft UAV (Unmanned Aerial Vehicle), is considered with two diverent methods. The first applies the Maximum Principle of optimal control to derive closed-form analytical functions that describe the translational states for two different cases of nonholonomic constraints. Parametric optimisation is used to find the trajectories. Reachable sets are found numerically and a simple obstacle avoidance method is demonstrated for both cases. The second motion planning method found trajectories with polynomial basis functions that are parametrised by an abstract function between zero and one. This virtual time domain trajectory satisfied conditions placed on the boundary derivatives and followed a sequenceof desired waypoints. A process for finding a mapping function that converts the virtual domain trajectory into one on the standard time domain is developed to minimise the trajectory time whilst ensuring the motion remained feasible by enforcing bounds on the thrust required from each rotor. An algorithm that uses additional waypoints where necessary to ensure the trajectory does not collide with the gates that define the course is developed. A method for minimising the accumulated angular acceleration of the heading angle whilst remaining within a desired tolerance of the velocity vector angle is also described. Trajectory tracking is considered by modifying an existing quadrotor tracking controller on the Special Euclidean group SE(3) to include a Linear Extended State Observer that estimates and counteracts translational disturbances. The modified controller is shown to reduce the position tracking error in the presence of square wave, sinusoidal and wind disturbances.

Liu, Yong. "NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION". Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159.

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Sato, Kazuhiro. "An Algebraic Analysis Approach to Trajectory Tracking Control". 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/188865.

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Chebly, Alia. "Trajectory planning and tracking for autonomous vehicles navigation". Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2392/document.

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Les travaux de cette thèse portent sur la navigation des véhicules autonomes, notamment la planification de trajectoires et le contrôle du véhicule. En premier lieu, un modèle véhicule plan est développé en utilisant une technique de modélisation qui assimile le véhicule à un robot constitué de plusieurs corps articulés. La description géométrique du véhicule est basée sur la convention de Denavit-Hartenberg modifiée. Le modèle dynamique du véhicule est ensuite calculé en utilisant la méthode récursive de Newton-Euler, qui est souvent utilisée dans le domaine de robotique. La validation du modèle a été conduite sur le simulateur Scaner-Studio développé par Oktal pour les applications automobiles. Le modèle du véhicule développé est ensuite utilisé pour la synthèse de lois de commande couplées pour les dynamiques longitudinale et latérale du véhicule. Deux correcteurs sont proposés dans ce travail : le premier est basé sur les techniques de commande par Lyapunov, le second utilise une approche ”Immersion et Invariance”. Ces deux contrôleurs ont pour objectifs de suivre une trajectoire de référence donnée avec un profil de vitesse désirée, tout en tenant compte du couplage existant entre les dynamiques longitudinale et latérale du véhicule. En effet, le contrôle couplé est nécessaire pour garantir la sécurité du véhicule autonome surtout lors de l’exécution des manœuvres couplées comme les manœuvres de changement de voie, les manœuvres d’évitement d’obstacles et les manœuvres exécutées dans les situations de conduite critiques. Les contrôleurs développés ont été validés en simulation sous Matlab/Simulink en utilisant des données expérimentales. Par la suite, ces contrôleurs ont été validés expérimentalement en utilisant le véhicule démonstrateur robotisé (Renault-Zoé) du laboratoire Heudiasyc financé par l’Equipex Robotex. En ce qui concerne la planification de trajectoires, une méthode de planification basée sur la méthode des tentacules sous forme de clothoides a été développée. En outre, une méthode de planification de manœuvres qui s’intéresse essentiellement à la manœuvre de dépassement a été mise en place, afin d’améliorer et de compléter la méthode locale des tentacules. Le planificateur local et le planificateur de manœuvres ont été ensuite combinés pour établir une stratégie de navigation complète. Cette stratégie a été validée par la suite sous Matlab/Simulink en utilisant le modèle de véhicule développé et le contrôleur basé sur Lyapunov
In this thesis, the trajectory planning and the control of autonomous vehicles are addressed. As a first step, a multi-body modeling technique is used to develop a four wheeled vehicle planar model. This technique considers the vehicle as a robot consisting of articulated bodies. The geometric description of the vehicle system is derived using the modified Denavit Hartenberg parameterization and then the dynamic model of the vehicle is computed by applying a recursive method used in robotics, namely Newton-Euler based Algorithm. The validation of the developed vehicle model was then conducted using an automotive simulator developed by Oktal, the Scaner-Studio simulator. The developed vehicle model is then used to derive coupled control laws for the lateral and the longitudinal vehicle dynamics. Two coupled controllers are proposed in this thesis: In the first controller, the control is designed using Lyapunov control techniques while in the second one an Immersion and Invariance approach is used. Both of the controllers aim to ensure a robust tracking of the reference trajectory and the desired speed while taking into account the strong coupling between the lateral and the longitudinal vehicle dynamics. In fact, the coupled controller is a key step for the vehicle safety handling, especially in coupled maneuvers such as lane-change maneuvers, obstacle avoidance maneuvers and combined maneuvers in critical driving situations. The developed controllers were validated in simulation under Matlab/Simulink using experimental data. Subsequently, an experimental validation of the proposed controllers was conducted using a robotized vehicle (Renault-ZOE) present in the Heudiasyc laboratory within the Equipex Robotex project. Concerning the trajectory planning, a local planning method based on the clothoid tentacles method is developed. Moreover, a maneuver planning strategy focusing on the overtaking maneuver is developed to improve and complete the local planning approach. The local and the maneuver planners are then combined in order to establish a complete navigation strategy. This strategy is then validated using the developed robotics vehicle model and the Lyapunov based controller under Matlab/Simulink

Glamheden, Mikael, e Simon Eriksson. "Autonomous Trajectory Tracking for a Differential Drive Vehicle". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239351.

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This paper explores controlling a two-wheeled differential drive vehicle using path planning algorithms and potential fields in order to track a target area while avoiding obstacles. Additionally, formation control was investigated using potential fields and a virtual structure approach separately. Finally, analysis of communication constraints in the form of sampling, disturbances and quantization are taken into account and theoretical or analysis results are given. It was concluded that the potential fields method result in an intuitive and dynamic controller that can be used to navigate within a large-scale and dynamic environment, as well as be used for formation control. The virtual structure approach is more robust when dealing with formation control, but it does not consider obstacle avoidance on its own.

Sansom, Eleanor Kate. "Tracking Meteoroids in the Atmosphere: Fireball Trajectory Analysis". Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/55061.

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This thesis improves and develops algorithms for fireball trajectory analysis. Stochastic estimators outside the current field of fireball modelling have been applied, from Kalman filters to 3D particle filters. These techniques are fully automated and rigorously incorporate errors, providing a means to routinely analyse fireball data in an unbiased manner.

Kahale, Elie. "Planification et commande d'une plate-forme aéroportée stationnaire autonome dédiée à la surveillance des ouvrages d'art". Thesis, Evry-Val d'Essonne, 2014. http://www.theses.fr/2014EVRY0016/document.

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Abstract (sommario):

Aujourd'hui, l'inspection des ouvrages d'art est réalisée de façon visuelle par des contrôleurs sur l'ensemble de la structure. Cette procédure est couteuse et peut être particulièrement dangereuse pour les intervenants. Pour cela, le développement du système de vision embarquée sur des drones est privilégié ces jours-ci afin de faciliter l'accès aux zones dangereuses.Dans ce contexte, le travail de cette thèse porte sur l'obtention des méthodes originales permettant la planification, la génération des trajectoires de référence, et le suivi de ces trajectoires par une plate-forme aéroportée stationnaire autonome. Ces méthodes devront habiliter une automatisation du vol en présence de perturbations aérologiques ainsi que des obstacles. Dans ce cadre, nous nous sommes intéressés à deux types de véhicules aériens capable de vol stationnaire : le dirigeable et le quadri-rotors.Premièrement, la représentation mathématique du véhicule volant en présence du vent a été réalisée en se basant sur la deuxième loi de Newton. Deuxièmement, la problématique de génération de trajectoire en présence de vent a été étudiée : le problème de temps minimal est formulé, analysé analytiquement et résolu numériquement. Ensuite, une stratégie de planification de trajectoire basée sur les approches de recherche opérationnelle a été développée.Troisièmement, le problème de suivi de trajectoire a été abordé. Une loi de commande non-linéaire robuste basée sur l'analyse de Lyapunov a été proposée. En outre, un pilote automatique basée sur les fonctions de saturations pour un quadri-rotors a été développée.Les méthodes et algorithmes proposés dans cette thèse ont été validés par des simulations
Today, the inspection of structures is carried out through visual assessments effected by qualified inspectors. This procedure is very expensive and can put the personal in dangerous situations. Consequently, the development of an unmanned aerial vehicle equipped with on-board vision systems is privileged nowadays in order to facilitate the access to unreachable zones.In this context, the main focus in the thesis is developing original methods to deal with planning, reference trajectories generation and tracking issues by a hovering airborne platform. These methods should allow an automation of the flight in the presence of air disturbances and obstacles. Within this framework, we are interested in two kinds of aerial vehicles with hovering capacity: airship and quad-rotors.Firstly, the mathematical representation of an aerial vehicle in the presence of wind has been realized using the second law of newton.Secondly, the question of trajectory generation in the presence of wind has been studied: the problem of minimal time was formulated, analyzed analytically and solved numerically. Then, a strategy of trajectory planning based on operational research approaches has been developed.Thirdly, the problem of trajectory tracking was carried out. A nonlinear robust control law based on Lyapunov analysis has been proposed. In addition, an autopilot based on saturation functions for quad-rotor crafts has been developed.All methods and algorithms proposed in this thesis have been validated through simulations

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Libri sul tema "Tracking trajectory":

Löber, Jakob. Optimal Trajectory Tracking of Nonlinear Dynamical Systems. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46574-6.

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Choi, Youngjin, e Wan Kyun Chung, a cura di. PID Trajectory Tracking Control for Mechanical Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-40041-7.

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Petropoulakis, L. Design of digital trajectory tracking systems for robotic manipulators. Salford: University of Salford, 1986.

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Galt, J. A. Digital distribution standard for NOAA trajectory analysis information. Seattle, Wash: Hazardous Materials Response and Assessment Division, Office of Ocean Resources Conservation and Assessment, National Oceanic and Atmospheric Administration, 1996.

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Abidin, Zainal. Design of digital high-accuracy trajectory tracking systems for multivariable plants. Salford: University of Salford, 1991.

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Ford, Kevin S. Optimizing aerobot exploration of Venus. Monterey, Calif: Naval Postgraduate School, 1997.

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Blom, H. A. P. A method and measures to evaluate trackers for air traffic control. Amsterdam: National Aerospace Laboratory, 1986.

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Contributors, Multiple, e Terry James. Trajectory: Tracking the Approaching Tribulation Storm. Defender Publishing, 2022.

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Choi, Youngjin, e Wan Kyun Chung. PID Trajectory Tracking Control for Mechanical Systems. Springer London, Limited, 2004.

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Löber, Jakob. Optimal Trajectory Tracking of Nonlinear Dynamical Systems. Springer, 2016.

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Capitoli di libri sul tema "Tracking trajectory":

Vanderborght, Bram. "Trajectory Tracking". In Springer Tracts in Advanced Robotics, 143–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13417-3_4.

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Ortega, Romeo, Antonio Loría, Per Johan Nicklasson e Hebertt Sira-Ramírez. "Trajectory tracking control". In Passivity-based Control of Euler-Lagrange Systems, 93–113. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-3603-3_4.

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Brogliato, Bernard. "Trajectory Tracking Feedback Control". In Communications and Control Engineering, 477–534. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28664-8_8.

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Delaplace, S., P. Blazevic, J. G. Fontaine, N. Pons e J. Rabit. "Trajectory Tracking for Mobile Robot". In Robotic Systems, 313–20. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2526-0_36.

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Seifried, Robert. "Trajectory Tracking of Multibody Systems". In Dynamics of Underactuated Multibody Systems, 113–66. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01228-5_4.

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Reiter, Alexander. "Optimal Path Tracking". In Optimal Path and Trajectory Planning for Serial Robots, 137–54. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-28594-4_5.

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Löber, Jakob. "Analytical Approximations for Optimal Trajectory Tracking". In Optimal Trajectory Tracking of Nonlinear Dynamical Systems, 119–93. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46574-6_4.

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de Luca, Alessandro, Fernando Nicolò e Giovanni Ulivi. "Trajectory Tracking in Flexible Robot Arms". In Systems, Models and Feedback: Theory and Applications, 17–34. Boston, MA: Birkhäuser Boston, 1992. http://dx.doi.org/10.1007/978-1-4757-2204-8_2.

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Amato, Ariel, Murad Haj, Mikhail Mozerov e Jordi Gonzàlez. "Trajectory Fusion for Multiple Camera Tracking". In Advances in Soft Computing, 19–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75175-5_3.

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Xu, Jianqiu, e Jiangang Zhou. "Detect Tracking Behavior Among Trajectory Data". In Advanced Data Mining and Applications, 872–78. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69179-4_64.

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Atti di convegni sul tema "Tracking trajectory":

"State tracking through optimized trajectory tracking". In Proceedings of the 1999 American Control Conference. IEEE, 1999. http://dx.doi.org/10.1109/acc.1999.786158.

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de Castro, Ricardo, e Jonathan Brembeck. "Supervised Trajectory Tracking Control". In 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018. http://dx.doi.org/10.1109/itsc.2018.8569377.

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Lindhe, Magnus, e Karl Henrik Johansson. "Communication-aware trajectory tracking". In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543417.

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Kelkar, A. G., e S. M. Joshi. "Trajectory Tracking of Multibody Spacecraft". In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0394.

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Abstract This paper addresses the problem of trajectory tracking of multibody spacecraft. The class of systems considered consists of a central body to which a number of articulated appendages are attached. Each appendage itself could be a serial chain of bodies. For the case of rigid multibody systems, nonlinear equations of motion are obtained for the tracking error dynamics. The quaternion representation is used for the central body attitude. A trajectory tracking control law is given, and is shown to provide global asymptotic stability of the tracking error. For the case of multibody flexible spacecraft in the attitude-hold configuration, it is shown that the closed-loop system remains ℒ2-stable under the proposed tracking control law.

Boucek, Zdenek, e Miroslav Flidr. "Interpolating Control Based Trajectory Tracking*". In 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2020. http://dx.doi.org/10.1109/icarcv50220.2020.9305511.

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Bedillion, M., e W. Messner. "Trajectory tracking for actuator arrays". In 2006 American Control Conference. IEEE, 2006. http://dx.doi.org/10.1109/acc.2006.1657323.

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Yi, Zhang, Yang Xiuxia, Zhao Hewei e Zhou Weiwei. "Tracking control for UAV trajectory". In 2014 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC). IEEE, 2014. http://dx.doi.org/10.1109/cgncc.2014.7007469.

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Gil-Martinez, M., e J. Rico-Azagra. "Multi-rotor robust trajectory tracking". In 2015 23th Mediterranean Conference on Control and Automation (MED). IEEE, 2015. http://dx.doi.org/10.1109/med.2015.7158854.

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Hoffmann, Gabriel, Steven Waslander e Claire Tomlin. "Quadrotor Helicopter Trajectory Tracking Control". In AIAA Guidance, Navigation and Control Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-7410.

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Avila, M. A., A. G. Loukianov e E. N. Sanchez. "Electro-hydraulic actuator trajectory tracking". In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1383858.

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Rapporti di organizzazioni sul tema "Tracking trajectory":

Cattani, Luis C., Paul J. Eagle, Zhud Lin e Xin Liu. Aircraft Trajectory Tracking and Prediction. Fort Belvoir, VA: Defense Technical Information Center, ottobre 1992. http://dx.doi.org/10.21236/ada259039.

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Erickson, Zachary K., Erik Fields, Melissa M. Omand, Leah Johnson, Andrew F. Thompson, Eric D’Asaro, Filipa Carvalho et al. EXPORTS North Atlantic eddy tracking. NASA STI Program and Woods Hole Oceanographic Institution, novembre 2022. http://dx.doi.org/10.1575/1912/29464.

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The EXPORTS North Atlantic field campaign (EXPORTS-NA) of May 2021 used a diverse array of ship-based and autonomous platforms to measure and quantify processes leading to carbon export in the open ocean. The success of this field program relied heavily on the ability to make measurements following a Lagrangian trajectory within a coherent, retentive eddy (Sections 1, 2). Identifying an eddy that would remain coherent and retentive over the course of a monthlong deployment was a significant challenge that the EXPORTS team faced. This report details the processes and procedures used by the primarily shore-based eddy tracking team to locate, track, and sample with autonomous assets such an eddy before and during EXPORTS-NA.

Evenson, Kelly R., Ty A. Ridenour, Jacqueline Bagwell e Robert D. Furberg. Sustaining Physical Activity Following Cardiac Rehabilitation Discharge. RTI Press, febbraio 2021. http://dx.doi.org/10.3768/rtipress.2021.rr.0043.2102.

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Because many patients reduce exercise following outpatient cardiac rehabilitation (CR), we developed an intervention to assist with the transition and evaluated its feasibility and preliminary efficacy using a one-group pretest–posttest design. Five CR patients were enrolled ~1 month prior to CR discharge and provided an activity tracker. Each week during CR they received a summary of their physical activity and steps. Following CR discharge, participants received an individualized report that included their physical activity and step history, information on specific features of the activity tracker, and encouraging messages from former CR patients for each of the next 6 weeks. Mixed model trajectory analyses were used to test the intervention effect separately for active minutes and steps modeling three study phases: pre-intervention (day activity tracking began to CR discharge), intervention (day following CR discharge to day when final report sent), and maintenance (day following the final report to ~1 month later). Activity tracking was successfully deployed and, with weekly reports following CR, may offset the usual decline in physical activity. When weekly reports ceased, a decline in steps/day occurred. A scaled-up intervention with a more rigorous study design with sufficient sample size can evaluate this approach further.

Mathew, Jijo K., Christopher M. Day, Howell Li e Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of these sampling techniques is to employ filtering techniques to remove outliers associated with trip chaining, but not remove important features in the data associated with incidents or traffic congestion. This paper describes a curated data set that was developed from high-fidelity GPS trajectory data. The curated data contained 31,621 vehicle observations spanning 42 days; 2550 observations had travel times greater than 3 minutes more than normal. From this baseline data set, outliers were determined using GPS waypoints to determine if the vehicle left the route. Two performance measures were identified for evaluating three outlier-filtering algorithms by the proportion of true samples rejected and proportion of outliers correctly identified. The effectiveness of the three methods over 10-minute sampling windows was also evaluated. The curated data set has been archived in a digital repository and is available online for others to test outlier-filtering algorithms.

Monetary Policy Report - April 2022. Banco de la República, giugno 2022. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2022.

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Macroeconomic summary Annual inflation continued to rise in the first quarter (8.5%) and again outpaced both market expectations and the technical staff’s projections. Inflation in major consumer price index (CPI) baskets has accelerated year-to-date, rising in March at an annual rate above 3%. Food prices (25.4%) continued to contribute most to rising inflation, mainly affected by a deterioration in external supply and rising costs of agricultural inputs. Increases in transportation prices and in some utility rates (energy and gas) can explain the acceleration in regulated items prices (8.3%). For its part, the increase in inflation excluding food and regulated items (4.5%) would be the result of shocks in supply and external costs that have been more persistent than expected, the effects of indexation, accumulated inflationary pressures from the exchange rate, and a faster-than-anticipated tightening of excess productive capacity. Within the basket excluding food and regulated items, external inflationary pressures have meaningfully impacted on goods prices (6.4%), which have been accelerating since the last quarter of 2021. Annual growth in services prices (3.8%) above the target rate is due primarily to food away from home (14.1%), which was affected by significant increases in food and utilities prices and by a rise in the legal monthly minimum wage. Housing rentals and other services prices also increased, though at rates below 3%. Forecast and expected inflation have increased and remain above the target rate, partly due to external pressures (prices and costs) that have been more persistent than projected in the January report (Graphs 1.1 and 1.2). Russia’s invasion of Ukraine accentuated inflationary pressures, particularly on international prices for certain agricultural goods and inputs, energy, and oil. The current inflation projection assumes international food prices will increase through the middle of this year, then remain high and relatively stable for the remainder of 2022. Recovery in the perishable food supply is forecast to be less dynamic than previously anticipated due to high agricultural input prices. Oil prices should begin to recede starting in the second half of the year, but from higher levels than those presented in the previous report. Given the above, higher forecast inflation could accentuate indexation effects and increase inflation expectations. The reversion of a rebate on value-added tax (VAT) applied to cleaning and hygiene products, alongside the end of Colombia’s COVID-19 health emergency, could increase the prices of those goods. The elimination of excess productive capacity on the forecast horizon, with an output gap close to zero and somewhat higher than projected in January, is another factor to consider. As a consequence, annual inflation is expected to remain at high levels through June. Inflation should then decline, though at a slower pace than projected in the previous report. The adjustment process of the monetary policy rate wouldcontribute to pushing inflation and its expectations toward the target on the forecast horizon. Year-end inflation for 2022 is expected to be around 7.1%, declining to 4.8% in 2023. Economic activity again outperformed expectations. The technical staff’s growth forecast for 2022 has been revised upward from 4.3% to 5% (Graph 1.3). Output increased more than expected in annual terms in the fourth quarter of 2021 (10.7%), driven by domestic demand that came primarily because of private consumption above pre-pandemic levels. Investment also registered a significant recovery without returning to 2019 levels and with mixed performance by component. The trade deficit increased, with significant growth in imports similar to that for exports. The economic tracking indicator (ISE) for January and February suggested that firstquarter output would be higher than previously expected and that the positive demand shock observed at the end of 2021 could be fading slower than anticipated. Imports in consumer goods, retail sales figures, real restaurant and hotel income, and credit card purchases suggest that household spending continues to be dynamic, with levels similar to those registered at the end of 2021. Project launch and housing starts figures and capital goods import data suggest that investment also continues to recover but would remain below pre-pandemic levels. Consumption growth is expected to decelerate over the year from high levels reached over the last two quarters. This would come amid tighter domestic and external financial conditions, the exhaustion of suppressed demand, and a deterioration of available household income due to increased inflation. Investment is expected to continue to recover, while the trade deficit should tighten alongside high oil and other export commodity prices. Given all of the above, first-quarter economic growth is now expected to be 7.2% (previously 5.2%) and 5.0% for 2022 as a whole (previously 4.3%). Output growth would continue to moderate in 2023 (2.9%, previously 3.1%), converging similar to long-term rates. The technical staff’s revised projections suggest that the output gap would remain at levels close to zero on the forecast horizon but be tighter than forecast in January (Graph 1.4). These estimates continue to be affected by significant uncertainty associated with geopolitical tensions, external financial conditions, Colombia’s electoral cycle, and the COVID-19 pandemic. External demand is now projected to grow at a slower pace than previously expected amid increased global inflationary pressures, high oil prices, and tighter international financial conditions than forecast in January. The Russian invasion of Ukraine and its inflationary effects on prices for oil and certain agricultural goods and inputs accentuated existing global inflationary pressures originating in supply restrictions and increased international costs. A decline in the supply of Russian oil, low inventory levels, and continued production limits on behalf of the Organization of Petroleum Exporting Countries and its allies (OPEC+) can explain increased projected oil prices for 2022 (USD 100.8/barrel, previously USD 75.3) and 2023 (USD 86.8/barrel, previously USD 71.2). The forecast trajectory for the U.S. Federal Reserve (Fed) interest rate has increased for this and next year to reflect higher real and expected inflation and positive performance in the labormarket and economic activity. The normalization of monetary policy in various developed and emerging market economies, more persistent supply and cost shocks, and outbreaks of COVID-19 in some Asian countries contributed to a reduction in the average growth outlook for Colombia’s trade partners for 2022 (2.8%, previously 3.3%) and 2023 (2.4%, previously 2.6%). In this context, the projected path for Colombia’s risk premium increased, partly due to increased geopolitical global tensions, less expansionary monetary policy in the United States, an increase in perceived risk for emerging markets, and domestic factors such as accumulated macroeconomic imbalances and political uncertainty. Given all the above, external financial conditions are tighter than projected in January report. External forecasts and their impact on Colombia’s macroeconomic scenario continue to be affected by considerable uncertainty, given the unpredictability of both the conflict between Russia and Ukraine and the pandemic. The current macroeconomic scenario, characterized by high real inflation levels, forecast and expected inflation above 3%, and an output gap close to zero, suggests an increased risk of inflation expectations becoming unanchored. This scenario offers very limited space for expansionary monetary policy. Domestic demand has been more dynamic than projected in the January report and excess productive capacity would have tightened more quickly than anticipated. Headline and core inflation rose above expectations, reflecting more persistent and important external shocks on supply and costs. The Russian invasion of Ukraine accentuated supply restrictions and pressures on international costs. This partly explains the increase in the inflation forecast trajectory to levels above the target in the next two years. Inflation expectations increased again and are above 3%. All of this increased the risk of inflation expectations becoming unanchored and could generate indexation effects that move inflation still further from the target rate. This macroeconomic context also implies reduced space for expansionary monetary policy. 1.2 Monetary policy decision Banco de la República’s board of directors (BDBR) continues to adjust its monetary policy. In its meetings both in March and April of 2022, it decided by majority to increase the monetary policy rate by 100 basis points, bringing it to 6.0% (Graph 1.5).