Дисертації з теми "Moving obstacles"
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Dintelmann, Eva. "Fluids in the exterior domain of several moving obstacles /." Berlin : wvb, Wiss. Verl, 2007. http://www.wvberlin.de/data/inhalt/dintelmann.html.
Повний текст джерелаChiaroni, Florent. "Weakly supervised learning for image classification and potentially moving obstacles analysis." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASC006.
Повний текст джерелаIn the context of autonomous vehicle perception, the interest of the research community for deep learning approaches has continuously grown since the last decade. This can be explained by the fact that deep learning techniques provide nowadays state-of-the-art prediction performances for several computer vision challenges. More specifically, deep learning techniques can provide rich semantic information concerning the complex visual patterns encountered in autonomous driving scenarios. However, such approaches require, as their name implies, to learn on data. In particular, state-of-the-art prediction performances on discriminative tasks often demand hand labeled data of the target application domain. Hand labeling has a significant cost, while, conversely, unlabeled data can be easily obtained in the autonomous driving context. It turns out that a category of learning strategies, referred to as weakly supervised learning, enables to exploit partially labeled data. Therefore, we aim in this thesis at reducing as much as possible the hand labeling requirement by proposing weakly supervised learning techniques.We start by presenting a type of learning methods which are self-supervised. They consist of substituting hand-labels by upstream techniques able to automatically generate exploitable training labels. Self-supervised learning (SSL) techniques have proven their usefulness in the past for offroad obstacles avoidance and path planning through changing environments. However, SSL techniques still leave the door open for detection, segmentation, and classification of static potentially moving obstacles.Consequently, we propose in this thesis three novel weakly supervised learning methods with the final goal to deal with such road users through an SSL framework. The first two proposed contributions of this work aim at dealing with partially labeled image classification datasets, such that the labeling effort can be only focused on our class of interest, the positive class. Then, we propose an approach which deals with training data containing a high fraction of wrong labels, referred to as noisy labels. Next, we demonstrate the potential of such weakly supervised strategies for detection and segmentation of potentially moving obstacles
Kolomenskiy, Dmitry. "Numerical modelling of lows past moving obstacles : Application to the aerodynamics of insect flight." Aix-Marseille 1, 2010. http://www.theses.fr/2001AIX11034.
Повний текст джерелаThe dissertation presents theoretical and numerical studies of unsteady flows relevant to insect flapping flight. Much emphasis is put on the development of a numerical method for modelling incompressible viscous flows past multiple moving solid obstacles. The Navier–Stokes equations are solved using a Fourier pseudo-spectral discretization. Solid obstacles are modelled with the volume penalization method. An original approach is proposed for interpolation of the time-dependent penalization mask function, which takes advantage of the spectral discretization. Both two- and three-dimensional solvers have been developed, which differ in some implementation aspects. Notably, the three-dimensional code is adapted for massively parallel computers. The newly-developed numerical method is employed in a study of the Lighthill–Weis- Fogh mechanism, an unsteady aerodynamic mechanism used by some insects. That study begins, however, with the inviscid fluid model first considered by Lighthill. A transition from fling to sweep is analysed, when the connectivity of the domain changes. Then, modifications due to viscosity are explored. Important viscous effects are found near the trailing edges. The flow field near the hinge, observed in numerical simulations, is explained theoretically by local analysis of the Stokes equation. The importance of the three-dimensional effects is assessed. Numerical simulations are performed at two different values of the Reynolds number, Re = 128 and 1400, typical for insects of different size. The flow during fling is shown to be in reasonable agreement with the two-dimensional approximation. After the wings move apart, three-dimensional effects become essential. The penalization model has been extended to solve the problem of solid bodies falling through a fluid. Numerical simulations at Re = 10, 100 and 1000 have shown that decreasing Re has a stabilizing effect on the free fall dynamics
An, Vatana. "A THIRD-ORDER DIFFERENTIAL STEERING ROBOT AND TRAJECTORY GENERATION IN THE PRESENCE OF MOVING OBSTACLES." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2433.
Повний текст джерелаM.S.E.E.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering
Elias, Ricardo. "A VIRTUAL REALITY VISUALIZATION OFAN ANALYTICAL SOLUTION TOMOBILE ROBOT TRAJECTORY GENERATIONIN THE PRESENCE OF MOVING OBSTACLES." Master's thesis, University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2438.
Повний текст джерелаM.S.E.E.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering MSEE
Lalonde, Jeffrey R. "Monocular Obstacle Detection for Moving Vehicles." Thesis, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/20582.
Повний текст джерелаKunogi, Noriyuki. "Scattering problem for the Maxwell equations outside a moving obstacle." 京都大学 (Kyoto University), 2008. http://hdl.handle.net/2433/135996.
Повний текст джерелаLimongiello, Alessandro. "Real-time video analysis from a mobile platform : moving object and obstacle detection." Lyon, INSA, 2007. http://www.theses.fr/2007ISAL0036.
Повний текст джерелаNous présentons un système de vision pour la navigation autonome d’une plateforme mobile. Ce système est en mesure d’interagir avec l’espace immédiatement environnant, en reconnaissant les obstacles et les objets en mouvement et en construisant une vision stable du monde extérieur. Le système est composé de trois composants : la représentation dans l’espace environnant ; la détection et l’évitement des obstacles et l’analyse comportementale. La contribution majeure de ce travail concerne la représentation « perceptive » de l’espace, c’est-à-dire une représentation qui est comparée à l’objectif final de la navigation autonome. Cette représentation est basée sur le paradigme de la vision stéréo et elle permet de déterminer dans la scène les obstacles et les objets en mouvement. Notre méthode fournit la profondeur moyenne par région. L’estimation de la position des régions est suffisamment précise pour la navigation et le système est assez rapide pour les applications en temps réel
Karlsson, Samuel. "Monocular vision-based obstacle avoidance for Micro Aerial Vehicles." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80906.
Повний текст джерелаWu, Jianhua. "Dynamic Path Planning of an Omni-directional Robot in a Dynamic Environment." Ohio University / OhioLINK, 2005. http://www.ohiolink.edu/etd/view.cgi?ohiou1113839523.
Повний текст джерелаJackson, James Scott. "Enabling Autonomous Operation of Micro Aerial Vehicles Through GPS to GPS-Denied Transitions." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8709.
Повний текст джерелаWang, Bihao. "Geometrical and contextual scene analysis for object detection and tracking in intelligent vehicles." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2197/document.
Повний текст джерелаFor autonomous or semi-autonomous intelligent vehicles, perception constitutes the first fundamental task to be performed before decision and action/control. Through the analysis of video, Lidar and radar data, it provides a specific representation of the environment and of its state, by extracting key properties from sensor data with time integration of sensor information. Compared to other perception modalities such as GPS, inertial or range sensors (Lidar, radar, ultrasonic), the cameras offer the greatest amount of information. Thanks to their versatility, cameras allow intelligent systems to achieve both high-level contextual and low-level geometrical information about the observed scene, and this is at high speed and low cost. Furthermore, the passive sensing technology of cameras enables low energy consumption and facilitates small size system integration. The use of cameras is however, not trivial and poses a number of theoretical issues related to how this sensor perceives its environmen. In this thesis, we propose a vision-only system for moving object detection. Indeed,within natural and constrained environments observed by an intelligent vehicle, moving objects represent high risk collision obstacles, and have to be handled robustly. We approach the problem of detecting moving objects by first extracting the local contextusing a color-based road segmentation. After transforming the color image into illuminant invariant image, shadows as well as their negative influence on the detection process can be removed. Hence, according to the feature automatically selected onthe road, a region of interest (ROI), where the moving objects can appear with a high collision risk, is extracted. Within this area, the moving pixels are then identified usin ga plane+parallax approach. To this end, the potential moving and parallax pixels a redetected using a background subtraction method; then three different geometrical constraints : the epipolar constraint, the structural consistency constraint and the trifocaltensor are applied to such potential pixels to filter out parallax ones. Likelihood equations are also introduced to combine the constraints in a complementary and effectiveway. When stereo vision is available, the road segmentation and on-road obstacles detection can be refined by means of the disparity map with geometrical cues. Moreover, in this case, a robust tracking algorithm combining image and depth information has been proposed. If one of the two cameras fails, the system can therefore come back to a monocular operation mode, which is an important feature for perception system reliability and integrity. The different proposed algorithms have been tested on public images data set with anevaluation against state-of-the-art approaches and ground-truth data. The obtained results are promising and show that the proposed methods are effective and robust on the different traffic scenarios and can achieve reliable detections in ambiguous situations
"Moving Obstacle Avoidance for Unmanned Aerial Vehicles." Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.35967.
Повний текст джерелаDissertation/Thesis
Doctoral Dissertation Computer Science 2015
Chen, Li-Wei, and 陳立偉. "Study of Moving obstacle Detection at Railway Crossing by Machine Vision." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/962ua3.
Повний текст джерела長榮大學
職業安全與衛生學系碩士班
98
The railway transportation is quite important, and has integrated into the populace's lives in Taiwan. The crossing where a railway and a road intersect is the region that the road users and the train meet. The railway has brought us convenience, but on the contrary has also caused many traffic accidents each year. Presently the railway in Taiwan spans approximately 1,100 kilometers and has 650 level crossings, which means that approximately every 1.7 kilometers there will be a crossing on the tracks. Therefore, most road users has many chances to pass through the crossings everyday.. According to the statistics 432 accidents occurred at all crossings in Taiwan during 2004-2008 and claimed 132 deaths and 137 wounds, which shows that some citizens have not obeyed the traffic regulations and that the safety protection measures on the crossings still need to be improved. The existing protection devices of crossing include those traditional signs, flash lights, horns , barriers and direction indicators of the approaching trains. These devices only give warmings to the road users but can not do anything about intrusions and temporary stops at the crossing. Among the recently equipped devices emergency buttons need the passers-by to operate manually. In the state of news, people may stall or even forget to operate the buttons, which actually reduces the effect of this device. As matter of fact, there are more hoaxes than real emergency conditions. Other recently developed devices can automatically detect obstacles, which include photoelectric sensors, inductive coils, radar and ultrasonic systems. However, these safety devices have some defects. Such as the blind spots to the photoelectric instrument, the climate and the interference sensitive to the inductive coils, the surrounding interference and the restrictive regulations to the radar signals, as well as the wind disturbance to the ultrasound devices. This study utilizes a 1394 CCD camera and the LabVIEW Graphic programming language to process the images of a railway crossing miniature. The developed system is designed to be a redundant safety measure which is able to detect the existence of obstacles at the crossing, along with the characteristics of moving obstacles. If the crossing is not clear, the system will send alarms immediately to avoid the accident and reduce its severity. Therefore the safety of the crew and passengers on the trains as well as the road users can be further assured.
Lin, Shih-Wen, and 林士文. "Analysis of Collision-Free Motion between a Robot Manipulator and a Moving Obstacle." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/08325082865447629000.
Повний текст джерелаSu, Ying-Chuan, and 蘇英銓. "A Study on Outdoor Guidance of Autonomous Land Vehiclesby Detecting the Moving Obstacle." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/h6k2q4.
Повний текст джерела國立臺北科技大學
機電整合研究所
96
In this paper, we develop the system of autonomous land vehicles (ALV) by computer vision with artificial intelligent (AI) based on optical flow method. It makes ALV adapted to the complex environment. This system can verify the motion obstacle and estimate its movement, and then making path strategy to avoid collision. Our algorithm of ALV has three parts, image capture system, static object analyzed system, and motion object detection system, respectively. We set ALV navigates at an outdoor environment automatically. In computer vision analyzed, we present a method that use Lucas and Kanade''s Optical flow equation, then we obtain the optical flow map, by using three-dimension histogram (3-D histogram) to gather statistics of our moving object, checking our optical vectors group, separating the optical vectors of obstacle and background, and use morphological process to segment the moving object. We segment them and use first-order linear equation to calculate the relationship between ALV and the motion obstacle. At last, calculate the collision time between the moving object and ALV and makes strategy to avoid collision with obstacle. Finally, our experiment shows the method avoiding collision with moving object efficiently when ALV moving on its way.
Lin, Chung Chang, and 林仲章. "The Design and Application for the Moving Obstacle-Avoidance Path Planning of Robot by Using AutoCAD Interface Platform." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/97911911028770031613.
Повний текст джерела國立臺北科技大學
機電整合研究所
92
In this study, AutoCAD 2002 is used as a working media. Through VBA and 3D solid drawing function inside AutoCAD, an interface software of moving obstacle-avoidance path planning for Mitsubishi Robot RV-E2 is established. First, user needs to input the information which include both start point and end point for end effecter of robot、the dimension of both obstacle and end effecter、the moving speed of both obstacle and robot、the start point of obstacle. Second, We build the 3D solid model of obstacle and robot in the Working space of AutoCAD. Then according to these input data, simulation for the moving motion is made to check if any interference (collision) by using “Interference” command of AutoCAD is happened. All coordinates of trajectory just pass through are recorded. Here we offer an intelligent graph interference theory to determine the best path of obstacle-Avoidance. This non-collision path made by using this moving simulation method is shown on the screen of AutoCAD. Finally, We can transfer the calculated path data through RS-232 to the controller of robot to drive it. The actual moving obstacle-Avoidance motion path and the physical motion path are feedback to the AutoCAD screen immediately for comparison with the theoretical simulation path.
Αρβανιτάκης, Ιωάννης. "Πλοήγηση, σχεδιασμός τροχιάς και έλεγχος κινούμενου ρομπότ". Thesis, 2009. http://nemertes.lis.upatras.gr/jspui/handle/10889/2509.
Повний текст джерелаThe present thesis deals with the navigation of moving robots. Granted an area with obstacles and target, it deals with the creation of an algorithm for guiding the robot through space at target, avoiding obstacles during movement. It focuses on two-wheeled robots and analyzes step by step the process of finding a path, creating the trajectory and controlling the robot.