Zobrazeno 1 - 10
of 10 949
pro vyhledávání: '"A. Tamim"'
In this paper, we present an approach for learning collision-free robot trajectories in the presence of moving obstacles. As a first step, we train a backup policy to generate evasive movements from arbitrary initial robot states using model-free rei
Externí odkaz:
http://arxiv.org/abs/2411.05784
Gaussian Process Latent Variable Models (GPLVMs) have proven effective in capturing complex, high-dimensional data through lower-dimensional representations. Recent advances show that using Riemannian manifolds as latent spaces provides more flexibil
Externí odkaz:
http://arxiv.org/abs/2410.20850
By incorporating physical consistency as inductive bias, deep neural networks display increased generalization capabilities and data efficiency in learning nonlinear dynamic models. However, the complexity of these models generally increases with the
Externí odkaz:
http://arxiv.org/abs/2410.18868
In this paper, we present a novel approach for learning bimanual manipulation actions from human demonstration by extracting spatial constraints between affordance regions, termed affordance constraints, of the objects involved. Affordance regions ar
Externí odkaz:
http://arxiv.org/abs/2410.08848
Autonomous unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can effectively execute surveillance, connectivity, and computing services to ground users (GUs). These missions require trajectory planning, UAV-GUs association, task offloading, next-
Externí odkaz:
http://arxiv.org/abs/2410.06627
Autor:
Bärmann, Leonard, DeChant, Chad, Plewnia, Joana, Peller-Konrad, Fabian, Bauer, Daniel, Asfour, Tamim, Waibel, Alex
Verbalization of robot experience, i.e., summarization of and question answering about a robot's past, is a crucial ability for improving human-robot interaction. Previous works applied rule-based systems or fine-tuned deep models to verbalize short
Externí odkaz:
http://arxiv.org/abs/2409.17702
Autor:
Marquardt, Charlotte, Schulz, Arne, Dezman, Miha, Kurz, Gunther, Stein, Thorsten, Asfour, Tamim
Online adaptation of exoskeleton control based on muscle activity sensing is a promising way to personalize exoskeletons based on the user's biosignals. While several electromyography (EMG) based methods have been shown to improve joint torque estima
Externí odkaz:
http://arxiv.org/abs/2409.11061
Bimanual manipulation is challenging due to precise spatial and temporal coordination required between two arms. While there exist several real-world bimanual systems, there is a lack of simulated benchmarks with a large task diversity for systematic
Externí odkaz:
http://arxiv.org/abs/2407.00278
Autor:
Dinh, Tu Anh, Mullov, Carlos, Bärmann, Leonard, Li, Zhaolin, Liu, Danni, Reiß, Simon, Lee, Jueun, Lerzer, Nathan, Ternava, Fabian, Gao, Jianfeng, Röddiger, Tobias, Waibel, Alexander, Asfour, Tamim, Beigl, Michael, Stiefelhagen, Rainer, Dachsbacher, Carsten, Böhm, Klemens, Niehues, Jan
With the rapid development of Large Language Models (LLMs), it is crucial to have benchmarks which can evaluate the ability of LLMs on different domains. One common use of LLMs is performing tasks on scientific topics, such as writing algorithms, que
Externí odkaz:
http://arxiv.org/abs/2406.10421
By leveraging the kernel trick in the output space, kernel-induced losses provide a principled way to define structured output prediction tasks for a wide variety of output modalities. In particular, they have been successfully used in the context of
Externí odkaz:
http://arxiv.org/abs/2406.09253