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BABIUCH, Marek; KRYS, Václav and BOBOVSKÝ, Zdenko. Learning and Reconstruction of Mobile Robot Trajectories with LSTM Autoencoders: A Data-Driven Framework for Real-World
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Conf. on Intelligent Robots and Systems, 2017, pp. 3075–3080. [8] O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” in IEEE Int. Conf.
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to a goal or home position solely based on visual information, has received increasing attention and played an important role in many applications in the field of mobile
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simulation and virtual control models for complete and complex mobile robot manipulation platforms. VI. REASONING, PERCEPTION, AND LEARNING Let us now consider how
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2016. [21] M. Giftthaler, F. Farshidian, T. Sandy, L. Stadelmann, and J. Buchli, “Efficient Kinematic Planning for Mobile Manipulators with Non- holonomic Constraints
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a TOMASKOVA, M.. Use of mobile fans to ensure the safety of road tunnels during fire. In: Transport Means - Proceedings of the International Conference 2019. 2019.
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method is often used for the localization of mobile robots (UGVs, UAVs, cars) to enable their autonomy or for extended reality devices (headsets, cellphones) for
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localization is to estimate from which position and orientation a given image was taken. This method is often used for the localization of mobile robots (UGVs, UAVs,
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HONUS, Stanislav. Zařízení pro výzkum spalování alternativních pevných paliv. 2019. Detail PETRŮ, Jana; MRKVICA, Ivan; ZLÁMAL, Tomáš; ČEP, Robert and PAGÁČ, Marek. Mobile
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HONUS, Stanislav. Zařízení pro výzkum spalování alternativních pevných paliv. 2019. Detail PETRŮ, Jana; MRKVICA, Ivan; ZLÁMAL, Tomáš; ČEP, Robert and PAGÁČ, Marek. Mobile
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P., Dohnálek, P., Peterek, T.: Mobile Sensor Data Classification Using GM-SOM, Advances in Intelligent Systems and Computing. Volume 210, 12, pp. 487-496 (2013).
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pořádané VŠB-TUO: - antistresový míček - vůně do auta - hledač klíčů - píšťalka - žárovka - stojánek na mobil - prupiska - a další Propagační předměty VŠB-TUO byly
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P., Dohnálek, P., Peterek, T.: Mobile Sensor Data Classification Using GM-SOM, Advances in Intelligent Systems and Computing. Volume 210, 12, pp. 487-496 (2013).
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P., Dohnálek, P., Peterek, T.: Mobile Sensor Data Classification Using GM-SOM, Advances in Intelligent Systems and Computing. Volume 210, 12, pp. 487-496 (2013).
http://kat354nas3.vsb.cz/iros2018/media/files/1140.pdf
2011. [4] A. Tahirovic, G. Magnani, "A roughness-based rrt for mobile robot navigation planning", IFAC World Congress, vol. 18, pp. 5944-5949, 2001. [5] S.M. LaValle
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I_2020_03_Lampa_Samolejova.pdf. Detail ČECH, M.; WICHER, P.; LENORT, R.; MALČIC, T.; DAVID, J.; HOLMAN, D.; STAŠ, D. a ZÁRUBA, Jiří. Autonomous mobile robot technology
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zajišťujících provoz 4G a 5G mobilních sítí. Tento výzkum probíhá na základě spolupráce s centrem kompetence pro vývoj sítí provozovaným T-Mobile Czech Republic
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SLÍVA, Aleš. Hydrometallurgical recycling process for mobile phone printed circuit boards using ozone. Online. Metals. 2021, Vol. 11, no. 5, p. 820. ISSN 2075-4701.
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by new effective technologies, such as GPS, satellite imaging and mobile mapping. It is important to compare the cost of producing photogrammetric products, such
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technologies. For the preparation of the module “Railway”, mobile sources of threat (of the rail transport of dangerous substances) will be mapped in the area of