Academic literature on the topic 'Moving obstacles'
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Journal articles on the topic "Moving obstacles"
Aivar, M. Pilar, Eli Brenner, and Jeroen B. J. Smeets. "Avoiding moving obstacles." Experimental Brain Research 190, no. 3 (July 16, 2008): 251–64. http://dx.doi.org/10.1007/s00221-008-1475-9.
Full textGraffstein, Jerzy. "The Avoiding Manoeuvre Against Aggregated Group of Obstacles Moving Around the Airplane." Pomiary Automatyka Robotyka 25, no. 1 (March 31, 2021): 5–12. http://dx.doi.org/10.14313/par_239/5.
Full textBurnett, Nicholas P., Marc A. Badger, and Stacey A. Combes. "Wind and obstacle motion affect honeybee flight strategies in cluttered environments." Journal of Experimental Biology 223, no. 14 (June 19, 2020): jeb222471. http://dx.doi.org/10.1242/jeb.222471.
Full textLakshmi, Dr K. Prasanna. "Motion Planning of Moving Robots Amongst Static Obstacles." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 167–70. http://dx.doi.org/10.15373/22778179/may2013/57.
Full textKownacki, Cezary, and Leszek Ambroziak. "A New Multidimensional Repulsive Potential Field to Avoid Obstacles by Nonholonomic UAVs in Dynamic Environments." Sensors 21, no. 22 (November 11, 2021): 7495. http://dx.doi.org/10.3390/s21227495.
Full textFujimori, A. "Navigation of mobile robots with collision avoidance for moving obstacles." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 219, no. 1 (February 1, 2005): 99–110. http://dx.doi.org/10.1243/095440705x9416.
Full textHoshino, Satoshi, and Tomoki Yoshikawa. "Motion Planning of Mobile Robots for Occluded Obstacles." Journal of Robotics and Mechatronics 30, no. 3 (June 20, 2018): 485–92. http://dx.doi.org/10.20965/jrm.2018.p0485.
Full textBeghin, Luisa, and Enzo Orsingher. "Moving randomly amid scattered obstacles." Stochastics 82, no. 2 (April 2010): 201–29. http://dx.doi.org/10.1080/17442500903359163.
Full textVaĭnberg, B. R. "SCATTERING BY PERIODICALLY MOVING OBSTACLES." Mathematics of the USSR-Sbornik 73, no. 1 (February 28, 1992): 289–304. http://dx.doi.org/10.1070/sm1992v073n01abeh002546.
Full textWilliams, Robert L., and Jianhua Wu. "Dynamic Obstacle Avoidance for an Omnidirectional Mobile Robot." Journal of Robotics 2010 (2010): 1–14. http://dx.doi.org/10.1155/2010/901365.
Full textDissertations / Theses on the topic "Moving obstacles"
Dintelmann, Eva. "Fluids in the exterior domain of several moving obstacles /." Berlin : wvb, Wiss. Verl, 2007. http://www.wvberlin.de/data/inhalt/dintelmann.html.
Full textChiaroni, Florent. "Weakly supervised learning for image classification and potentially moving obstacles analysis." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASC006.
Full textIn 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.
Full textThe 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.
Full textM.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.
Full textM.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.
Full textKunogi, Noriyuki. "Scattering problem for the Maxwell equations outside a moving obstacle." 京都大学 (Kyoto University), 2008. http://hdl.handle.net/2433/135996.
Full textLimongiello, Alessandro. "Real-time video analysis from a mobile platform : moving object and obstacle detection." Lyon, INSA, 2007. http://www.theses.fr/2007ISAL0036.
Full textNous 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.
Full textWu, 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.
Full textBooks on the topic "Moving obstacles"
Professional Environmental Seminar (1st 1994 Cambridge, England). Moving forward: Overcoming the obstacles to a sustainable transport policy : proceedings of the first Professional Environmental Seminar held on Friday 25th February 1994 at the Møller Centre, Cambridge. Cambridge: White Horse Press, 1994.
Find full textMoving Obstacles. Policy Press, 1996.
Find full textWang, Chao, Alexey S. Matveev, Andrey V. Savkin, and Michael Hoy. Safe Robot Navigation among Moving and Steady Obstacles. Elsevier Science & Technology Books, 2015.
Find full textSafe Robot Navigation Among Moving and Steady Obstacles. Elsevier, 2016. http://dx.doi.org/10.1016/c2014-0-04846-0.
Full textWang, Chao, Alexey S. Matveev, Andrey V. Savkin, and Michael Hoy. Safe Robot Navigation among Moving and Steady Obstacles. Elsevier Science & Technology Books, 2015.
Find full textMurphy, L. S., L. F. Welch, and Eugene C. Doll. Moving up the Yield Curve: Advances and Obstacles. Wiley & Sons, Limited, John, 2015.
Find full textWard, Terrae. In Transition: Becoming Successful in Moving Through Life's Obstacles. Independently Published, 2018.
Find full textSharir, Micha, and Jacob T. Schwartz. On the Case of the Piano Movers' Problems: V. the Case of a Rod Moving in Three-Dimensional Space Amidst Polyhedral Obstacles. Creative Media Partners, LLC, 2018.
Find full textNestler, Eric J. New Approaches for Treating Depression. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0030.
Full textKitch, Sally L. Addressing Afghanistan’s Problems. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252038709.003.0009.
Full textBook chapters on the topic "Moving obstacles"
DiMarzio, J. F. "Moving a Character with Obstacles." In Android Game Recipes, 167–74. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-5765-3_13.
Full textCooper, Jeffery. "A Scattering Theory for Moving Obstacles *." In Functional Analysis, Holomorphy, and Approximation Theory, 11–19. Boca Raton: CRC Press, 2020. http://dx.doi.org/10.1201/9781003072577-2.
Full textQian, Shaohua, Joo Kooi Tan, Hyoungseop Kim, Seiji Ishikawa, and Takashi Morie. "Obstacles Extraction Using a Moving Camera." In Computer Vision - ACCV 2012 Workshops, 441–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37484-5_36.
Full textTeles da Silva, A. F., and D. H. Peregrine. "Wave-Breaking due to Moving Submerged Obstacles." In Breaking Waves, 333–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84847-6_38.
Full textvan den Berg, Jur, and Mark Overmars. "Planning the Shortest Safe Path Amidst Unpredictably Moving Obstacles." In Springer Tracts in Advanced Robotics, 103–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68405-3_7.
Full textAguilar, Wilbert G., Leandro Álvarez, Santiago Grijalva, and Israel Rojas. "Monocular Vision-Based Dynamic Moving Obstacles Detection and Avoidance." In Intelligent Robotics and Applications, 386–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27541-9_32.
Full textAnthimopoulou, M., and N. Aspragathos. "Kinematic Control of Planar Redundant Manipulators Moving Between Obstacles." In Advances in Robot Kinematics, 380–91. Vienna: Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-4433-6_43.
Full textWang, Zhiyong, and Sisi Zlatanova. "An A*-Based Search Approach for Navigation Among Moving Obstacles." In Intelligent Systems for Crisis Management, 17–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33218-0_2.
Full textMin, Hyeun-Jeong, and Sung-Bae Cho. "Bayesian Inference Driven Behavior Network Architecture for Avoiding Moving Obstacles." In Lecture Notes in Computer Science, 214–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552451_29.
Full textMohannad, Al-Khatib, and Jean J. Saade. "A Data-Driven Fuzzy Approach to Robot Navigation Among Moving Obstacles." In Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents, 109–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44491-2_17.
Full textConference papers on the topic "Moving obstacles"
Amano, N., H. Hashimoto, M. Higashiguchi, and Y. Kimura. "Detection of moving obstacles on moving vehicle." In 1999 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. IEEE, 1999. http://dx.doi.org/10.1109/aim.1999.803307.
Full textde Lamadrid, James G. "Avoidance System for Moving Obstacles." In Cambridge Symposium_Intelligent Robotics Systems, edited by Nelson Marquina and William J. Wolfe. SPIE, 1987. http://dx.doi.org/10.1117/12.937811.
Full textZhuang, Jiayuan, Yuhang Zhang, Peihong Xu, Yi Zhao, Jing Luo, and Shengqing Song. "Multiple Moving Obstacles Avoidance for USV using Velocity Obstacle Method." In 2021 IEEE International Conference on Unmanned Systems (ICUS). IEEE, 2021. http://dx.doi.org/10.1109/icus52573.2021.9641331.
Full textHaug, Edward J., Frederick A. Adkins, and Dan I. Coroian. "Domains of Mobility for a Planar Body Moving Among Obstacles." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1602.
Full textRajashekaraiah, Gangadhar, Hakki Erhan Sevil, and Atilla Dogan. "PTEM Based Moving Obstacle Detection and Avoidance for an Unmanned Ground Vehicle." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5330.
Full textZhu, Xiaoyuan, Jian Chen, Yan Ma, Jianqiang Deng, and Yuexuan Wang. "Predictive Motion Planning for Autonomous Vehicles With Geometric Constraints via Convex Optimization." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3169.
Full textBis, Rachael, Huei Peng, and Galip Ulsoy. "Velocity Occupancy Space: Robot Navigation and Moving Obstacle Avoidance With Sensor Uncertainty." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2570.
Full textCherubini, Andrea, Boris Grechanichenko, Fabien Spindler, and Francois Chaumette. "Avoiding moving obstacles during visual navigation." In 2013 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2013. http://dx.doi.org/10.1109/icra.2013.6631003.
Full textJavid, Ghasem Amini, Mohammad Durali, and Alireza Kasaaizadeh. "Overtaking Stationary and Moving Obstacles for Autonomous Ground Vehicles." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95437.
Full textKooshkbaghi, Marzieh, and Farzaneh Abdollahi. "Coverage control considering unknown moving obstacles avoidance." In 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM). IEEE, 2014. http://dx.doi.org/10.1109/icrom.2014.6990882.
Full textReports on the topic "Moving obstacles"
Sumpter, Cameron, and Yuslikha K. Wardhani. Hopes and Hurdles for Indonesia’s National Action Plan to Prevent Violent Extremism. RESOLVE Network, March 2022. http://dx.doi.org/10.37805/pn2022.2.sea.
Full textCowell, Chandler, Michael P. Gallaher, Justin Larson, and Aaron Schwartz. The Potential for SolarPowered Groundwater Irrigation in Sub-Saharan Africa: An Exploratory Analysis. RTI Press, November 2022. http://dx.doi.org/10.3768/rtipress.2022.op.0079.2211.
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