Tesis sobre el tema "Systèmes de localisation en temps réel (RTLS)"
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Abid, Mohamed Amine. "Systèmes de localisation en temps réel basés sur les réseaux de communication sans fil". Thèse, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/8820.
Texto completoBarbosa, Nogueira Evanaska Maria. "Conception d'un système d'antennes pour la localisation en temps réel avec réseau de capteurs sans fils". Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00981583.
Texto completoBenouakta, Amina. "Conception de systèmes antennaires pour applications de supervision et de localisation dans l'Internet des objets industriel". Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4011.
Texto completoThis thesis is part of the concept of the Internet of Things (IoT), object identification, and traceability in so-called complex environments through Ultra-Wide Band (UWB) technology known for its high temporal precision. The objective is to contribute to the advancement of real-time UWB-based localization systems through the design and optimization of UWB antennas that are reconfigurable, multi-standards, and multi-functions. Therefore, any localization system integrating the optimized antennas will have improved localization quality and new functionalities.The main contributions developed in this thesis involve enhancements to real-time localization systems (RTLS) based on UWB technology: design and fabrication of frequency reconfigurable UWB antennas; design and fabrication of a multi-standard localization electronic board (UWB and Long Range - LoRa); experimental study of RTLS systems incorporating the designed antennas and validation of the evolution of the localization in terms of extended reading ranges, detectability of objects without prior knowledge of their orientations, and improved location accuracy through the attenuation of multi-path signals
Marsit, Nadhem. "Traitement des requêtes dépendant de la localisation avec des contraintes de temps réel". Toulouse 3, 2007. http://thesesups.ups-tlse.fr/106/.
Texto completoIn last years, the mobility of units achieved an increasing development. One of the direct consequences in the database field is the appearance of new types of queries such as Location Dependent Queries (LDQ) (e. G. An ambulance driver asks for the closest hospital). These queries raise problems which have been considered by several researches. Despite the intensive work related to this field, the different types of queries studied so far do not meet all the needs of location based applications. In fact these works don’t take into account the real time aspect required by certain location based applications. These new requirements generate new types of queries such as mobile queries with real time constraints. Taking into account mobility and real time constraints is an important problem to deal with. Hence, our main objective is to propose a solution for considering real time constraints while location dependent query processing. First, we propose a language for expressing different type of queries. Then, we design a software architecture allowing to process location dependent queries with real time constraints. The modules of this architecture are designed to be implemented on top of existent DBMS (e. G. Oracle). We propose methods to take into account location of mobile client and his displacement after sending the query. We also propose methods in order to maximise the percentage of queries respecting their deadlines. Finally we validate our proposal by implementing the proposed methods and evaluating their performance
Abramik, Stanisław. "Base de connaissance des défauts des systèmes électriques pour systèmes experts : contribution à l'étude du diagnostic de défaillance des convertisseurs statiques en temps réel". Toulouse, INPT, 2003. http://www.theses.fr/2003INPT030H.
Texto completoMeilland, Maxime. "Cartographie RGB-D dense pour la localisation visuelle temps-réel et la navigation autonome". Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2012. http://tel.archives-ouvertes.fr/tel-00686803.
Texto completoRullan, Lara José Luis. "Conception et implantation embarquée d'un système de localisation en utilisant les signaux radio pour la stabilisation d'un mini drone". Compiègne, 2011. http://www.theses.fr/2011COMP1984.
Texto completoThe Unmanned Aerial Vehicles are complex and difficult dynamic systems to control. In spite of the efforts realized on the stabilization approaches (nested saturation, back-stepping, etc. ), the control laws have been always focused to stabilize the orientation of the vehicle and few works has been developed to estimate its position. Since real measurements are noisy and are not directly observable or measurable from the sensors, the estimation of the position is a difficult problem to resolve. Numerous approaches have been proposed for position’s estimation. In particular, vision and GPS have been explored in indoor and outdoor, respectively. However, there remain many challenges to its application in UAVs. This dissertation presents a solution to the problem of location of UAV indoor using radio signals. The k-nearest neighbor (KNN) algorithm, the least squares algorithm and the Extended Kalman filter have been tested and validated in real time. The performances of the algorithms were validated during hover flight and path following flight of a mini helicopter. In order to validate the algorithms, I developed a mini helicopter with four rotors (quad rotor) with the computer architecture for implementing onboard embedded control laws for its stability and for the implementation of localization tasks
Picard, Quentin. "Proposition de mécanismes d'optimisation des données pour la perception temps-réel dans un système embarqué hétérogène". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG039.
Texto completoThe development of autonomous systems has an increasing need for perception of the environment in embedded systems. Autonomous cars, drones, mixed reality devices have limited form factor and a restricted budget of power consumption for real-time performances. For instance, those use cases have a budget in the range of 300W-10W, 15W-10W and 10W-10mW respectively. This thesis is focused on autonomous and mobile systems with a budget of 10mW to 15W with the use of imager sensors and the inertial measurement unit (IMU). Simultaneous Localization And Mapping (SLAM) provides accurate and robust perception of the environment in real-time without prior knowledge for autonomous and mobile systems. The thesis aims at the real-time execution of the whole SLAM system composed of advanced perception functions, from localization to 3D reconstruction, with restricted hardware resources. In this context, two main questions are raised to answer the challenges of the literature. How to reduce the resource requirements of advanced perception functions? What is the SLAM pipeline partitioning for the heterogeneous system that integrates several computing units, from the embedded chip in the imager, to the near-sensor processing (FPGA) and in the embedded platform (ARM, embedded GPU)?. The first issue addressed in the thesis is about the need to reduce the hardware resources used by the SLAM pipeline, from the sensor output to the 3D reconstruction. In this regard, the work described in the manuscript provides two main contributions. The first one presents the processing in the embedded chip with an impact on the image characteristics by reducing the dynamic range. The second has an impact on the management of the image flow injected in the SLAM pipeline with a near-sensor processing. The first contribution aims at reducing the memory footprint of the SLAM algorithms with the evaluation of the pixel dynamic reduction on the accuracy and robustness of real-time localization and 3D reconstruction. The experiments show that we can reduce the input data up to 75% corresponding to 2 bits per pixel while maintaining a similar accuracy than the baseline 8 bits per pixel. Those results have been obtained with the evaluation of the accuracy and robustness of four SLAM algorithms on two databases. The second contribution aims at reducing the amount of data injected in SLAM with a decimation strategy to control the input frame rate, called the adaptive filtering. Data are initially injected in constant rate (20 frames per second). This implies a consumption of energy, memory, bandwidth and increases the complexity of calculation. Can we reduce this amount of data ? In SLAM, the accuracy and the number of operations depend on the movement of the system. With the linear and angular accelerations from the IMU, data are injected based on the movement of the system. Those key images are injected with the adaptive filtering approach (AF). Although the results depend on the difficulty of the chosen database, the experiments describe that the AF allows the decimation of up to 80% of the images while maintaining low localization and reconstruction errors similar to the baseline. This study shows that in the embedded context, the peak memory consumption is reduced up to 92%
Birem, Merwan. "Localisation et détection de fermeture de boucle basées saillance visuelle : algorithmes et architectures matérielles". Thesis, Clermont-Ferrand 2, 2015. http://www.theses.fr/2015CLF22558/document.
Texto completoIn several tasks of robotics, vision is considered to be the essential element by which the perception of the environment or the interaction with other users can be realized. However, the potential artifacts in the captured images make the task of recognition and interpretation of the visual information extremely complicated. It is therefore very important to use robust, stable and high repeatability rate primitives to achieve good performance. This thesis deals with the problems of localization and loop closure detection for a mobile robot using visual saliency. The results in terms of accuracy and efficiency of localization and closure detection applications are evaluated and compared to the results obtained with the approaches provided in literature, both applied on different sequences of images acquired in outdoor environnement. The main drawback with the models proposed for the extraction of salient regions is their computational complexity, which leads to significant processing time. To obtain a real-time processing, we present in this thesis also the implementation of the salient region detector on the reconfigurable platform DreamCam
Karam, Nadir. "Agrégation de données décentralisées pour la localisation multi-véhicules". Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2009. http://tel.archives-ouvertes.fr/tel-00724489.
Texto completoRoyer, Eric. "Cartographie 3D et localisation par vision monoculaire pour la navignation autonome d'un robot mobile". Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2006. http://tel.archives-ouvertes.fr/tel-00698908.
Texto completoGiraud, Denis. "Diagnostic des systèmes industriels complexes par agrégation de méthodes : application à une station d'épuration". Nancy 1, 1998. http://www.theses.fr/1998NAN10002.
Texto completoEl, bouazzaoui Imad. "Hardware Software Co-design of an Embedded RGB-D SLAM System". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST156.
Texto completoVision sensors with color and depth hâve recently gained popularity. Autonomous ve- hicles benefit from new 3D perception methods thanks to these sensors. We hâve investigated the various processing stages of the System to make contributions at the sensor-algorithm coupling and computing architecture levels. This study began by conducting a thorough experimental analysis of the impact of sensor acquisition modalities on locali zation accuracy. We introduced RGB-D HOOFR- SLAM, which was assessed using a self-collected RGB-D dataset. We compared the measurement results to those of the most advanced algorithms. The results revealed a significant réduction in lo calization errors and a significant gain in proces sing speed compared to the state-of-the-art stéréo and RGB-D algorithms. We proposed the implé mentation of the HOOFR SLAM front-end on an FPGA-based architecture. This innovative archi tecture delivers superior performance and a trade- off between power consumption and processing time
Tao, Zui. "Autonomous road vehicles localization using satellites, lane markings and vision". Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2261/document.
Texto completoEstimating the pose (position and attitude) in real-time is a key function for road autonomous vehicles. This thesis aims at studying vehicle localization performance using low cost automotive sensors. Three kinds of sensors are considered : dead reckoning (DR) sensors that already exist in modern vehicles, mono-frequency GNSS (Global navigation satellite system) receivers with patch antennas and a frontlooking lane detection camera. Highly accurate maps enhanced with road features are also key components for autonomous vehicle navigation. In this work, a lane marking map with decimeter-level accuracy is considered. The localization problem is studied in a local East-North-Up (ENU) working frame. Indeed, the localization outputs are used in real-time as inputs to a path planner and a motion generator to make a valet vehicle able to drive autonomously at low speed with nobody on-board the car. The use of a lane detection camera makes possible to exploit lane marking information stored in the georeferenced map. A lane marking detection module detects the vehicle’s host lane and provides the lateral distance between the detected lane marking and the vehicle. The camera is also able to identify the type of the detected lane markings (e.g., solid or dashed). Since the camera gives relative measurements, the important step is to link the measures with the vehicle’s state. A refined camera observation model is proposed. It expresses the camera metric measurements as a function of the vehicle’s state vector and the parameters of the detected lane markings. However, the use of a camera alone has some limitations. For example, lane markings can be missing in some parts of the navigation area and the camera sometimes fails to detect the lane markings in particular at cross-roads. GNSS, which is mandatory for cold start initialization, can be used also continuously in the multi-sensor localization system as done often when GNSS compensates for the DR drift. GNSS positioning errors can’t be modeled as white noises in particular with low cost mono-frequency receivers working in a standalone way, due to the unknown delays when the satellites signals cross the atmosphere and real-time satellites orbits errors. GNSS can also be affected by strong biases which are mainly due to multipath effect. This thesis studies GNSS biases shaping models that are used in the localization solver by augmenting the state vector. An abrupt bias due to multipath is seen as an outlier that has to be rejected by the filter. Depending on the information flows between the GNSS receiver and the other components of the localization system, data-fusion architectures are commonly referred to as loosely coupled (GNSS fixes and velocities) and tightly coupled (raw pseudoranges and Dopplers for the satellites in view). This thesis investigates both approaches. In particular, a road-invariant approach is proposed to handle a refined modeling of the GNSS error in the loosely coupled approach since the camera can only improve the localization performance in the lateral direction of the road. Finally, this research discusses some map-matching issues for instance when the uncertainty domain of the vehicle state becomes large if the camera is blind. It is challenging in this case to distinguish between different lanes when the camera retrieves lane marking measurements.As many outdoor experiments have been carried out with equipped vehicles, every problem addressed in this thesis is evaluated with real data. The different studied approaches that perform the data fusion of DR, GNSS, camera and lane marking map are compared and several conclusions are drawn on the fusion architecture choice
Yu, Chunlei. "Contribution to evidential models for perception grids : application to intelligent vehicle navigation". Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2293.
Texto completoFor intelligent vehicle applications, a perception system is a key component to characterize in real-time a model of the driving environment at the surrounding of the vehicle. When modeling the environment, obstacle information is the first feature that has to be managed since collisions can be fatal for the other road users or for the passengers on-board the considered vehicle. Characterization of occupation space is therefore crucial but not sufficient for autonomous vehicles since the control system needs to find the navigable space for safe trajectory planning. Indeed, in order to run on public roads with other users, the vehicle needs to follow the traffic rules which are, for instance, described by markings painted on the carriageway. In this work, we focus on an ego-centered grid-based approach to model the environment. The objective is to include in a unified world model obstacle information with semantic road rules. To model obstacle information, occupancy is handled by interpreting the information of different sensors into the values of the cells. To model the semantic of the navigable space, we propose to introduce the notion of lane grids which consist in integrating semantic lane information into the cells of the grid. The combination of these two levels of information gives a refined environment model. When interpreting sensor data into obstacle information, uncertainty inevitably arises from ignorance and errors. Ignorance is due to the perception of new areas and errors come from noisy measurements and imprecise pose estimation. In this research, the belief function theory is adopted to deal with uncertainties and we propose evidential models for different kind of sensors like lidars and cameras. Lane grids contain semantic lane information coming from lane marking information for instance. To this end, we propose to use a prior map which contains detailed road information including road orientation and lane markings. This information is extracted from the map by using a pose estimate provided by a localization system. In the proposed model, we integrate lane information into the grids by taking into account the uncertainty of the estimated pose. The proposed algorithms have been implemented and tested on real data acquired on public roads. We have developed algorithms in Matlab and C++ using the PACPUS software framework developed at the laboratory
Zinoune, Clément. "Autonomous integrity monitoring of navigation maps on board intelligent vehicles". Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP1972/document.
Texto completoSeveral Intelligent Vehicles capabilities from Advanced Driving Assistance Systems (ADAS) to Autonomous Driving functions depend on a priori information provided by navigation maps. Whilst these were intended for driver guidance as they store road network information, today they are even used in applications that control vehicle motion. In general, the vehicle position is projected onto the map to relate with links in the stored road network. However, maps might contain faults, leading to navigation and situation understanding errors. Therefore, the integrity of the map-matched estimates must be monitored to avoid failures that can lead to hazardous situations. The main focus of this research is the real-time autonomous evaluation of faults in navigation maps used in intelligent vehicles. Current passenger vehicles are equipped with proprioceptive sensors that allow estimating accurately the vehicle state over short periods of time rather than long trajectories. They include receiver for Global Navigation Satellite System (GNSS) and are also increasingly equipped with exteroceptive sensors like radar or smart camera systems. The challenge resides on evaluating the integrity of the navigation maps using vehicle on board sensors. Two types of map faults are considered: Structural Faults, addressing connectivity (e.g., intersections). Geometric Faults, addressing geographic location and road geometry (i.e. shape). Initially, a particular structural navigation map fault is addressed: the detection of roundabouts absent in the navigation map. This structural fault is problematic for ADAS and Autonomous Driving. The roundabouts are detected by classifying the shape of the vehicle trajectory. This is stored for use in ADAS and Autonomous Driving functions on future vehicle trips on the same area. Next, the geometry of the map is addressed. The main difficulties to do the autonomous integrity monitoring are the lack of reliable information and the low level of redundancy. This thesis introduces a mathematical framework based on the use of repeated vehicle trips to assess the integrity of map information. A sequential test is then developed to make it robust to noisy sensor data. The mathematical framework is demonstrated theoretically including the derivation of definitions and associated properties. Experiments using data acquired in real traffic conditions illustrate the performance of the proposed approaches