Zobrazeno 1 - 10
of 362
pro vyhledávání: '"P. Esterle"'
Countless terms of service (ToS) are being signed everyday by users all over the world while interacting with all kinds of apps and websites. More often than not, these online contracts spanning double-digit pages are signed blindly by users who simp
Externí odkaz:
http://arxiv.org/abs/2409.00077
In recent advancements in machine learning, federated learning allows a network of distributed clients to collaboratively develop a global model without needing to share their local data. This technique aims to safeguard privacy, countering the vulne
Externí odkaz:
http://arxiv.org/abs/2407.12410
Autor:
Hoffmann, Jasper, Fernandez, Diego, Brosseit, Julien, Bernhard, Julian, Esterle, Klemens, Werling, Moritz, Karg, Michael, Boedecker, Joschka
Model predictive control (MPC) is a powerful, optimization-based approach for controlling dynamical systems. However, the computational complexity of online optimization can be problematic on embedded devices. Especially, when we need to guarantee fi
Externí odkaz:
http://arxiv.org/abs/2404.18863
Digital Twins represent a new and disruptive technology, where digital replicas of (cyber)-physical systems operate for long periods of time alongside their (cyber)-physical counterparts, with enabled bi-directional communication between them. Howeve
Externí odkaz:
http://arxiv.org/abs/2304.07328
Federated Learning offers a way to train deep neural networks in a distributed fashion. While this addresses limitations related to distributed data, it incurs a communication overhead as the model parameters or gradients need to be exchanged regular
Externí odkaz:
http://arxiv.org/abs/2302.02949
Images and video frames captured by cameras placed throughout smart cities are often transmitted over the network to a server to be processed by deep neural networks for various tasks. Transmission of raw images, i.e., without any form of compression
Externí odkaz:
http://arxiv.org/abs/2207.10155
Motion planning for urban environments with numerous moving agents can be viewed as a combinatorial problem. With passing an obstacle before, after, right or left, there are multiple options an autonomous vehicle could choose to execute. These combin
Externí odkaz:
http://arxiv.org/abs/2207.04418
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
Externí odkaz:
https://doaj.org/article/97e30fa47d6a4f998d68fe6f7518f7eb
Cooperatively planning for multiple agents has been proposed as a promising method for strategic and motion planning for automated vehicles. By taking into account the intent of every agent, the ego agent can incorporate future interactions with huma
Externí odkaz:
http://arxiv.org/abs/2109.15122
In this paper we present an experience report for the RMQFMU, a plug and play tool, that enables feeding data to/from an FMI2-based co-simulation environment based on the AMQP protocol. Bridging the co-simulation to an external environment allows on
Externí odkaz:
http://arxiv.org/abs/2107.01010