162 research outputs found

    Fast depth edge detection and edge based RGB-D SLAM

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    CARLA-Loc: Synthetic SLAM Dataset with Full-stack Sensor Setup in Challenging Weather and Dynamic Environments

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    The robustness of SLAM algorithms in challenging environmental conditions is crucial for autonomous driving, but the impact of these conditions are unknown while given the difficulty of arbitrarily changing the relevant environmental parameters of the same environment in the real world. Therefore, we propose CARLA-Loc, a synthetic dataset of challenging and dynamic environments built on CARLA simulator. We integrate multiple sensors into the dataset with strict calibration, synchronization and precise timestamping. 7 maps and 42 sequences are posed in our dataset with different dynamic levels and weather conditions. Objects in both stereo images and point clouds are well-segmented with their class labels. We evaluate 5 visual-based and 4 LiDAR-based approaches on varies sequences and analyze the effect of challenging environmental factors on the localization accuracy, showing the applicability of proposed dataset for validating SLAM algorithms

    Otomatikleştirilmiş rehberli araç sistemlerinin transport tekniğinde modellemesi

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    The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature.Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir

    Modeling Automated Guided Vehicle Systems in Material Handling

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    Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

    Modeling Automated Guided Vehicle Systems in Material Handling

    Get PDF
    Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

    Trajectory Servoing: Image-Based Trajectory Tracking without Absolute Positioning

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    The thesis describes an image based visual servoing (IBVS) system for a non-holonomic robot to achieve good trajectory following without real-time robot pose information and without a known visual map of the environment. We call it trajectory servoing. The critical component is a feature based, indirect SLAM method to provide a pool of available features with estimated depth and covariance, so that they may be propagated forward in time to generate image feature trajectories with uncertainty information for visual servoing. Short and long distance experiments show the benefits of trajectory servoing for navigating unknown areas without absolute positioning. Trajectory servoing is shown to be more accurate than SLAM pose-based feedback and further improved by a weighted least square controller using covariance from the underlying SLAM system.M.S

    Autonomous Simultaneous Localization and Mapping driven by Monte Carlo uncertainty maps-based navigation

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    This paper addresses the problem of implementing a Simultaneous Localization and Mapping (SLAM) algorithm combined with a non-reactive controller (such as trajectory following or path following). A general study showing the advantages of using predictors to avoid mapping inconsistences in autonomous SLAM architectures is presented. In addition, this paper presents a priority-based uncertainty map construction method of the environment by a mobile robot when executing a SLAM algorithm. The SLAM algorithm is implemented with an extended Kalman filter (EKF) and extracts corners (convex and concave) and lines (associated with walls) from the surrounding environment. A navigation approach directs the robot motion to the regions of the environment with the higher uncertainty and the higher priority. The uncertainty of a region is specified by a probability characterization computed at the corresponding representative points. These points are obtained by a Monte Carlo experiment and their probability is estimated by the sum of Gaussians method, avoiding the time-consuming map-gridding procedure. The priority is determined by the frame in which the uncertainty region was detected (either local or global to the vehicle's pose). The mobile robot has a non-reactive trajectory following controller implemented on it to drive the vehicle to the uncertainty points. SLAM real-time experiments in real environment, navigation examples, uncertainty maps constructions along with algorithm strategies and architectures are also included in this work.Fil: Auat Cheein, Fernando Alfredo. Universidad Técnica Federico Santa María; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pereira, Fernando M. Lobo. Universidad de Porto; PortugalFil: Di Sciascio, Fernando Agustín. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

    Present and Future of SLAM in Extreme Underground Environments

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    This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT competition. In particular, the paper has four main goals. First, we review the algorithms, architectures, and systems adopted by the teams; particular emphasis is put on lidar-centric SLAM solutions (the go-to approach for virtually all teams in the competition), heterogeneous multi-robot operation (including both aerial and ground robots), and real-world underground operation (from the presence of obscurants to the need to handle tight computational constraints). We do not shy away from discussing the dirty details behind the different SubT SLAM systems, which are often omitted from technical papers. Second, we discuss the maturity of the field by highlighting what is possible with the current SLAM systems and what we believe is within reach with some good systems engineering. Third, we outline what we believe are fundamental open problems, that are likely to require further research to break through. Finally, we provide a list of open-source SLAM implementations and datasets that have been produced during the SubT challenge and related efforts, and constitute a useful resource for researchers and practitioners.Comment: 21 pages including references. This survey paper is submitted to IEEE Transactions on Robotics for pre-approva

    An embedded particle filter SLAM implementation using an affordable platform

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    PostprintThe recent growth in robotics applications has put to evidence the need for autonomous robots. In order for a robot to be truly autonomous, it must be able to solve the navigation problem. This paper highlights the main features of a fully embedded particle filter SLAM system and introduces some novel ways of calculating a measurement likelihood. A genetic algorithm calibration approach is used to prevent parameter over-fitting and obtain more generalizable results. Finally, it is depicted how the developed SLAM system was used to autonomously perform a field covering task showing robustness and better performance than a reference system. Several lines of possible improvements to the present system are presented
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