Zobrazeno 1 - 10
of 9 498
pro vyhledávání: '"A. Remes"'
Amortized meta-learning methods based on pre-training have propelled fields like natural language processing and vision. Transformer-based neural processes and their variants are leading models for probabilistic meta-learning with a tractable objecti
Externí odkaz:
http://arxiv.org/abs/2410.15320
Though control algorithms for multirotor Unmanned Air Vehicle (UAV) are well understood, the configuration, parameter estimation, and tuning of flight control algorithms takes quite some time and resources. In previous work, we have shown that it is
Externí odkaz:
http://arxiv.org/abs/2409.01080
This paper presents a method to recover quadrotor UAV from a throw, when no control parameters are known before the throw. We leverage the availability of high-frequency rotor speed feedback available in racing drone hardware and software to find con
Externí odkaz:
http://arxiv.org/abs/2406.11723
Publikováno v:
Facilities, 2023, Vol. 42, Issue 15/16, pp. 17-29.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/F-01-2023-0003
Overactuated Tilt Rotor Unmanned Aerial Vehicles are renowned for exceptional wind resistance and a broad operational range, which poses complex control challenges due to non-affine dynamics. Traditional solutions employ multi-state switched logic co
Externí odkaz:
http://arxiv.org/abs/2311.09185
Autor:
Aniek M. van Gils, Antti Tolonen, Argonde C. van Harten, Sinthujah Vigneswaran, Frederik Barkhof, Leonie N. C. Visser, Juha Koikkalainen, Sanna-Kaisa Herukka, Steen Gregers Hasselbalch, Patrizia Mecocci, Anne M. Remes, Hilkka Soininen, Afina W. Lemstra, Charlotte E. Teunissen, Linus Jönsson, Jyrki Lötjönen, Wiesje M. van der Flier, Hanneke F. M. Rhodius-Meester
Publikováno v:
Alzheimer’s Research & Therapy, Vol 16, Iss 1, Pp 1-17 (2024)
Abstract Background The increasing prevalence of dementia and the introduction of disease-modifying therapies (DMTs) highlight the need for efficient diagnostic pathways in memory clinics. We present a data-driven approach to efficiently guide stepwi
Externí odkaz:
https://doaj.org/article/a2890bad16974239a6f09dd399617f9d
Utilizing wind hovering techniques of soaring birds can save energy expenditure and improve the flight endurance of micro air vehicles (MAVs). Here, we present a novel method for fully autonomous orographic soaring without a priori knowledge of the w
Externí odkaz:
http://arxiv.org/abs/2308.00565
Autor:
Huang, Daolang, Haussmann, Manuel, Remes, Ulpu, John, ST, Clarté, Grégoire, Luck, Kevin Sebastian, Kaski, Samuel, Acerbi, Luigi
Conditional Neural Processes (CNPs) are a class of metalearning models popular for combining the runtime efficiency of amortized inference with reliable uncertainty quantification. Many relevant machine learning tasks, such as in spatio-temporal mode
Externí odkaz:
http://arxiv.org/abs/2306.10915
We present a novel controller for fixed-wing UAVs that enables autonomous soaring in an orographic wind field, extending flight endurance. Our method identifies soaring regions and addresses position control challenges by introducing a target gradien
Externí odkaz:
http://arxiv.org/abs/2305.13891
Publikováno v:
Composites Part C: Open Access, Vol 15, Iss , Pp 100530- (2024)
In this paper, the nonlinear creep behaviour of additive-manufactured carbon fibre-reinforced polyethylene terephthalate (CF-PET) is characterised using experimental, theoretical and computational methods. The experimental approach investigates the i
Externí odkaz:
https://doaj.org/article/af967de4f4ec488a92f5de54c7cf8a0b