Littérature scientifique sur le sujet « Graph-based localization and mapping »
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Articles de revues sur le sujet "Graph-based localization and mapping"
Xiong, Hui, Youping Chen, Xiaoping Li et Bing Chen. « A two-level optimized graph-based simultaneous localization and mapping algorithm ». Industrial Robot : An International Journal 45, no 6 (15 octobre 2018) : 758–65. http://dx.doi.org/10.1108/ir-04-2018-0078.
Texte intégralXu, Hao, Huafei Sun, Yongqiang Cheng et Hao Liu. « Wireless sensor networks localization based on graph embedding with polynomial mapping ». Computer Networks 106 (septembre 2016) : 151–60. http://dx.doi.org/10.1016/j.comnet.2016.06.032.
Texte intégralZhu, Zihan, Yi Zhang, Weijun Wang, Wei Feng, Haowen Luo et Yaojie Zhang. « Adaptive Adjustment of Factor’s Weight for a Multi-Sensor SLAM ». Journal of Physics : Conference Series 2451, no 1 (1 mars 2023) : 012004. http://dx.doi.org/10.1088/1742-6596/2451/1/012004.
Texte intégralMukherjee, Shohin, Michael Kaess, Joseph N. Martel et Cameron N. Riviere. « EyeSAM : graph-based localization and mapping of retinal vasculature during intraocular microsurgery ». International Journal of Computer Assisted Radiology and Surgery 14, no 5 (21 février 2019) : 819–28. http://dx.doi.org/10.1007/s11548-019-01925-1.
Texte intégralRen, Zhuli, Liguan Wang et Lin Bi. « Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment ». Sensors 19, no 13 (1 juillet 2019) : 2915. http://dx.doi.org/10.3390/s19132915.
Texte intégralDai, Kai, Bohua Sun, Guanpu Wu, Shuai Zhao, Fangwu Ma, Yufei Zhang et Jian Wu. « LiDAR-Based Sensor Fusion SLAM and Localization for Autonomous Driving Vehicles in Complex Scenarios ». Journal of Imaging 9, no 2 (20 février 2023) : 52. http://dx.doi.org/10.3390/jimaging9020052.
Texte intégralZhang Tianxi, 张天喜, 周军 Zhou Jun, 廖华丽 Liao Huali et 杨跟 Yang Gen. « Simultaneous Localization and Mapping Strategy of Graph Optimization Based on Three-Dimensional Laser ». Laser & ; Optoelectronics Progress 56, no 20 (2019) : 201502. http://dx.doi.org/10.3788/lop56.201502.
Texte intégralWu, Xinzhao, Peiqing Li, Qipeng Li et Zhuoran Li. « Two-dimensional-simultaneous Localisation and Mapping Study Based on Factor Graph Elimination Optimisation ». Sustainability 15, no 2 (8 janvier 2023) : 1172. http://dx.doi.org/10.3390/su15021172.
Texte intégralXu, Shaoyan, Tao Wang, Congyan Lang, Songhe Feng et Yi Jin. « Graph-based visual odometry for VSLAM ». Industrial Robot : An International Journal 45, no 5 (20 août 2018) : 679–87. http://dx.doi.org/10.1108/ir-04-2018-0061.
Texte intégralOKADA, Nobuya, Daichi ABE, Satoshi SUZUKI, Kojiro IIZUKA et Takashi KAWAMURA. « 2A2-R04 Image and Shape features combined Landmarks based Graph SLAM(Localization and Mapping) ». Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2014 (2014) : _2A2—R04_1—_2A2—R04_4. http://dx.doi.org/10.1299/jsmermd.2014._2a2-r04_1.
Texte intégralThèses sur le sujet "Graph-based localization and mapping"
Agarwal, Pratik [Verfasser], et Wolfram [Akademischer Betreuer] Burgard. « Robust graph-based localization and mapping = Robuste Graph-basierte Lokalisierung und Kartierung ». Freiburg : Universität, 2015. http://d-nb.info/111980549X/34.
Texte intégralSünderhauf, Niko. « Robust optimization for simultaneous localization and mapping ». Thesis, Technischen Universitat Chemnitz, 2012. https://eprints.qut.edu.au/109667/1/109667.pdf.
Texte intégralSünderhauf, Niko. « Robust Optimization for Simultaneous Localization and Mapping ». Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-86443.
Texte intégralJama, Michal. « Monocular vision based localization and mapping ». Diss., Kansas State University, 2011. http://hdl.handle.net/2097/8561.
Texte intégralDepartment of Electrical and Computer Engineering
Balasubramaniam Natarajan
Dale E. Schinstock
In this dissertation, two applications related to vision-based localization and mapping are considered: (1) improving navigation system based satellite location estimates by using on-board camera images, and (2) deriving position information from video stream and using it to aid an auto-pilot of an unmanned aerial vehicle (UAV). In the first part of this dissertation, a method for analyzing a minimization process called bundle adjustment (BA) used in stereo imagery based 3D terrain reconstruction to refine estimates of camera poses (positions and orientations) is presented. In particular, imagery obtained with pushbroom cameras is of interest. This work proposes a method to identify cases in which BA does not work as intended, i.e., the cases in which the pose estimates returned by the BA are not more accurate than estimates provided by a satellite navigation systems due to the existence of degrees of freedom (DOF) in BA. Use of inaccurate pose estimates causes warping and scaling effects in the reconstructed terrain and prevents the terrain from being used in scientific analysis. Main contributions of this part of work include: 1) formulation of a method for detecting DOF in the BA; and 2) identifying that two camera geometries commonly used to obtain stereo imagery have DOF. Also, this part presents results demonstrating that avoidance of the DOF can give significant accuracy gains in aerial imagery. The second part of this dissertation proposes a vision based system for UAV navigation. This is a monocular vision based simultaneous localization and mapping (SLAM) system, which measures the position and orientation of the camera and builds a map of the environment using a video-stream from a single camera. This is different from common SLAM solutions that use sensors that measure depth, like LIDAR, stereoscopic cameras or depth cameras. The SLAM solution was built by significantly modifying and extending a recent open-source SLAM solution that is fundamentally different from a traditional approach to solving SLAM problem. The modifications made are those needed to provide the position measurements necessary for the navigation solution on a UAV while simultaneously building the map, all while maintaining control of the UAV. The main contributions of this part include: 1) extension of the map building algorithm to enable it to be used realistically while controlling a UAV and simultaneously building the map; 2) improved performance of the SLAM algorithm for lower camera frame rates; and 3) the first known demonstration of a monocular SLAM algorithm successfully controlling a UAV while simultaneously building the map. This work demonstrates that a fully autonomous UAV that uses monocular vision for navigation is feasible, and can be effective in Global Positioning System denied environments.
Cummins, Mark. « Probabilistic localization and mapping in appearance space ». Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:a34370f2-a2a9-40b5-9a2d-1c8c616ff07a.
Texte intégralLim, Yu-Xi. « Efficient wireless location estimation through simultaneous localization and mapping ». Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28219.
Texte intégralCommittee Chair: Owen, Henry; Committee Member: Copeland, John; Committee Member: Giffin, Jonathon; Committee Member: Howard, Ayanna; Committee Member: Riley, George.
Schaefer, Alexander [Verfasser], et Wolfram [Akademischer Betreuer] Burgard. « Highly accurate lidar-based mapping and localization for mobile robots ». Freiburg : Universität, 2020. http://d-nb.info/1207756016/34.
Texte intégralOliveira, Douglas Coelho Braga de. « Dynamic-object-aware simultaneous localization and mapping for augmented reality applications ». Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/8059.
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Realidade Aumentada (RA) é uma tecnologia que permite combinar objetos virtuais tridimensionais com um ambiente predominantemente real, de forma a construir um novo ambiente onde os objetos reais e virtuais podem interagir uns com os outros em tempo real. Para fazer isso, é necessário encontrar a pose do observador (câmera, HMD, óculos inteligentes, etc.) em relação a um sistema de coordenadas global. Geralmente, algum objeto físico conhecido é usado para marcar o referencial para as projeções e para a posição do observador. O problema de Localização e Mapeamento Simultâneo (SLAM) se origina da comunidade de robótica como uma condição necessária para se construir robôs verdadeiramente autônomos, capazes de se auto localizarem em um ambiente desconhecido ao mesmo tempo que constroem um mapa da cena observada a partir de informações capturadas por um conjunto de sensores. A principal contribuição do SLAM para a RA é permitir aplicações em ambientes despreparados, ou seja, sem marcadores. No entanto, ao eliminar o marcador, perdemos o referencial para a projeção dos objetos virtuais e a principal fonte de interação entre os elementos reais e virtuais. Embora o mapa gerado possa ser processado a fim de encontrar uma estrutura conhecida, como um plano predominante, para usá-la como referencial, isso ainda não resolve a questão das interações. Na literatura recente, encontramos trabalhos que integram um sistema de reconhecimento de objetos ao SLAM e incorporam tais objetos ao mapa. Frequentemente, assume-se um mapa estático, devido às limitações das técnicas envolvidas, de modo que o objeto é usado apenas para fornecer informações semânticas sobre a cena. Neste trabalho, propomos um novo framework que permite estimar simultaneamente a posição da câmera e de objetos para cada quadro de vídeo em tempo real. Dessa forma, cada objeto é independente e pode se mover pelo mapa livremente, assim como nos métodos baseados em marcadores, mas mantendo as vantagens que o SLAM fornece. Implementamos a estrutura proposta sobre um sistema SLAM de última geração a fim de validar nossa proposta e demonstrar a potencial aplicação em Realidade Aumentada.
Augmented Reality (AR) is a technology that allows combining three-dimensional virtual objects with an environment predominantly real in a way to build a new environment where both real and virtual objects can interact with each other in real-time. To do this, it is required to nd the pose of the observer (camera, HMD, smart glasses etc) in relation to a global coordinate system. Commonly, some well known physical object, called marker, is used to de ne the referential for both virtual objects and the observer's position. The Simultaneous Localization and Mapping (SLAM) problem borns from robotics community as a way to build truly autonomous robots by allowing they to localize themselves while they build a map of the observed scene from the input data of their coupled sensors. SLAM-based Augmented Reality is an active and evolving research line. The main contribution of the SLAM to the AR is to allow applications on unprepared environments, i.e., without markers. However, by eliminating the marker object, we lose the referential for virtual object projection and the main source of interaction between real and virtual elements. Although the generated map can be processed in order to nd a known structure, e.g. a predominant plane, to use it as the referential system, this still not solve for interactions. In the recent literature, we can found works that integrate an object recognition system to the SLAM in a way the objects are incorporated into the map. The SLAM map is frequently assumed to be static, due to limitations on techniques involved, so that on these works the object is just used to provide semantic information about the scene. In this work, we propose a new framework that allows estimating simultaneously the camera and object positioning for each camera image in real time. In this way, each object is independent and can move through the map as well as in the marker-based methods but with the SLAM advantages kept. We develop our proposed framework over a stateof- the-art SLAM system in order to evaluate our proposal and demonstrate potentials application in Augmented Reality.
Lee, Chun-Fan Computer Science & Engineering Faculty of Engineering UNSW. « Towards topological mapping with vision-based simultaneous localization and map building ». Awarded by:University of New South Wales. Computer Science & ; Engineering, 2008. http://handle.unsw.edu.au/1959.4/41551.
Texte intégralDroeschel, David Marcel [Verfasser]. « Efficient Methods for Lidar-based Mapping and Localization / David Marcel Droeschel ». Bonn : Universitäts- und Landesbibliothek Bonn, 2020. http://d-nb.info/122166929X/34.
Texte intégralLivres sur le sujet "Graph-based localization and mapping"
Dyer, Paul S., Carol A. Munro et Rosie E. Bradshaw. Fungal genetics. Sous la direction de Christopher C. Kibbler, Richard Barton, Neil A. R. Gow, Susan Howell, Donna M. MacCallum et Rohini J. Manuel. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198755388.003.0005.
Texte intégralChung, Moo K. Statistical and Computational Methods in Brain Image Analysis. Taylor & Francis Group, 2013.
Trouver le texte intégralStatistical and Computational Methods in Brain Image Analysis. Taylor & Francis Group, 2013.
Trouver le texte intégralChung, Moo K. Statistical and Computational Methods in Brain Image Analysis. Taylor & Francis Group, 2013.
Trouver le texte intégralChung, Moo K. Statistical and Computational Methods in Brain Image Analysis. Taylor & Francis Group, 2013.
Trouver le texte intégralPractical R for biologists : an introduction. Wallingford : CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0000.
Texte intégralChapitres de livres sur le sujet "Graph-based localization and mapping"
Werner, Martin. « Simultaneous Localization and Mapping in Buildings ». Dans Indoor Location-Based Services, 181–201. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10699-1_8.
Texte intégralWallgrün, Jan Oliver. « Voronoi Graph Matching for Robot Localization and Mapping ». Dans Transactions on Computational Science IX, 76–108. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16007-3_4.
Texte intégralZhu, Xiaorui, Youngshik Kim, Mark Andrew Minor et Chunxin Qiu. « Terrain-Inclination–Based Localization and Mapping ». Dans Autonomous Mobile Robots in Unknown Outdoor Environments, 187–204. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2017. | : CRC Press, 2017. http://dx.doi.org/10.1201/9781315151496-9.
Texte intégralZhou, Mu, Qiao Zhang, Zengshan Tian, Feng Qiu et Qing Jiang. « WLAN Localization Without Location Fingerprinting Using Logic Graph Mapping ». Dans Lecture Notes in Electrical Engineering, 545–56. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08991-1_56.
Texte intégralChatterjee, Amitava, Anjan Rakshit et N. Nirmal Singh. « Simultaneous Localization and Mapping (SLAM) in Mobile Robots ». Dans Vision Based Autonomous Robot Navigation, 167–206. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33965-3_7.
Texte intégralTsintotas, Konstantinos A., Loukas Bampis et Antonios Gasteratos. « The Revisiting Problem in Simultaneous Localization and Mapping ». Dans Online Appearance-Based Place Recognition and Mapping, 1–33. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09396-8_1.
Texte intégralLiu, Jiayi, Randy C. Hoover et Jeff S. McGough. « Mobile Fiducial-Based Collaborative Localization and Mapping (CLAM) ». Dans Proceedings of the 2020 USCToMM Symposium on Mechanical Systems and Robotics, 196–205. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43929-3_18.
Texte intégralGarcia-Fidalgo, Emilio, et Alberto Ortiz. « Probabilistic Appearance-Based Mapping and Localization Using Visual Features ». Dans Pattern Recognition and Image Analysis, 277–85. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_33.
Texte intégralWeikersdorfer, David, Raoul Hoffmann et Jörg Conradt. « Simultaneous Localization and Mapping for Event-Based Vision Systems ». Dans Lecture Notes in Computer Science, 133–42. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39402-7_14.
Texte intégralBryson, Mitch, et Salah Sukkarieh. « Inertial Sensor-Based Simultaneous Localization and Mapping for UAVs ». Dans Handbook of Unmanned Aerial Vehicles, 401–31. Dordrecht : Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_5.
Texte intégralActes de conférences sur le sujet "Graph-based localization and mapping"
Carlone, Luca, Rosario Aragues, Jose Castellanos et Basilio Bona. « A Linear Approximation for Graph-based Simultaneous Localization and Mapping ». Dans Robotics : Science and Systems 2011. Robotics : Science and Systems Foundation, 2011. http://dx.doi.org/10.15607/rss.2011.vii.006.
Texte intégralLeitinger, Erik, Florian Meyer, Fredrik Tufvesson et Klaus Witrisal. « Factor graph based simultaneous localization and mapping using multipath channel information ». Dans 2017 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2017. http://dx.doi.org/10.1109/iccw.2017.7962732.
Texte intégralYin, Jingchun, Luca Carlone, Stefano Rosa et Basilio Bona. « Graph-based robust localization and mapping for autonomous mobile robotic navigation ». Dans 2014 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2014. http://dx.doi.org/10.1109/icma.2014.6885953.
Texte intégralBeinschob, Patric, et Christoph Reinke. « Graph SLAM based mapping for AGV localization in large-scale warehouses ». Dans 2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2015. http://dx.doi.org/10.1109/iccp.2015.7312637.
Texte intégralMaddern, Will, Michael Milford et Gordon Wyeth. « Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph ». Dans 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012). IEEE, 2012. http://dx.doi.org/10.1109/iros.2012.6386186.
Texte intégralZhou, Mu, Qiao Zhang, Zengshan Tian, Kunjie Xu, Feng Qiu et Qi Wu. « Graph drawing based WLAN indoor mapping and localization using signal correlation via edge detection ». Dans 2015 IEEE International Wireless Symposium (IWS). IEEE, 2015. http://dx.doi.org/10.1109/ieee-iws.2015.7164524.
Texte intégralBabu, Benzun P. Wisely, David Cyganski et James Duckworth. « Gyroscope assisted scalable visual simultaneous localization and mapping ». Dans 2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS). IEEE, 2014. http://dx.doi.org/10.1109/upinlbs.2014.7033731.
Texte intégralZheng, Junyuan, Yuan He et Masaaki Kondo. « Exploiting Data Parallelism in Graph-Based Simultaneous Localization and Mapping : A Case Study with GPU Accelerations ». Dans HPC ASIA 2023 : International Conference on High Performance Computing in Asia-Pacific Region. New York, NY, USA : ACM, 2023. http://dx.doi.org/10.1145/3578178.3578237.
Texte intégralDanping, Jia, Duan Guangxue, Wang Nan, Zhou Zhigang, Zhong Zhenyu et Lei Huan. « Simultaneous Localization and Mapping based on Lidar ». Dans 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8833308.
Texte intégralMeghdari, A., K. Kobravi, H. Safyallah, M. Moeeni, Y. Khatami et H. Khasteh. « A New Approach to Sonar Based Indoor Mapping Localization ». Dans ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85269.
Texte intégralRapports d'organisations sur le sujet "Graph-based localization and mapping"
Christie, Benjamin, Osama Ennasr et Garry Glaspell. Autonomous navigation and mapping in a simulated environment. Engineer Research and Development Center (U.S.), septembre 2021. http://dx.doi.org/10.21079/11681/42006.
Texte intégralLee, W. S., Victor Alchanatis et Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, janvier 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
Texte intégralWan, Wei. A New Approach to the Decomposition of Incompletely Specified Functions Based on Graph Coloring and Local Transformation and Its Application to FPGA Mapping. Portland State University Library, janvier 2000. http://dx.doi.org/10.15760/etd.6582.
Texte intégralBennett, Alan B., Arthur A. Schaffer, Ilan Levin, Marina Petreikov et Adi Doron-Faigenboim. Manipulating fruit chloroplasts as a strategy to improve fruit quality. United States Department of Agriculture, janvier 2013. http://dx.doi.org/10.32747/2013.7598148.bard.
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