Zobrazeno 1 - 10
of 414
pro vyhledávání: '"Turčan P"'
Autor:
Talbot, William, Nubert, Julian, Tuna, Turcan, Cadena, Cesar, Dümbgen, Frederike, Tordesillas, Jesus, Barfoot, Timothy D., Hutter, Marco
Accurate, efficient, and robust state estimation is more important than ever in robotics as the variety of platforms and complexity of tasks continue to grow. Historically, discrete-time filters and smoothers have been the dominant approach, in which
Externí odkaz:
http://arxiv.org/abs/2411.03951
Autor:
Tuna, Turcan, Nubert, Julian, Pfreundschuh, Patrick, Cadena, Cesar, Khattak, Shehryar, Hutter, Marco
The ICP registration algorithm has been a preferred method for LiDAR-based robot localization for nearly a decade. However, even in modern SLAM solutions, ICP can degrade and become unreliable in geometrically ill-conditioned environments. Current so
Externí odkaz:
http://arxiv.org/abs/2408.11809
In the field of emotion analysis, much NLP research focuses on identifying a limited number of discrete emotion categories, often applied across languages. These basic sets, however, are rarely designed with textual data in mind, and culture, languag
Externí odkaz:
http://arxiv.org/abs/2407.12196
Autor:
Arora, Aashish, Turcan, Elsbeth
Data augmentation has the potential to improve the performance of machine learning models by increasing the amount of training data available. In this study, we evaluated the effectiveness of different data augmentation techniques for a multi-label e
Externí odkaz:
http://arxiv.org/abs/2406.05190
Autor:
Mattamala, Matías, Chebrolu, Nived, Casseau, Benoit, Freißmuth, Leonard, Frey, Jonas, Tuna, Turcan, Hutter, Marco, Fallon, Maurice
We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balance of endurance and low soil impact for forest applications. In this pa
Externí odkaz:
http://arxiv.org/abs/2404.14157
Autor:
Arm, Philip, Waibel, Gabriel, Preisig, Jan, Tuna, Turcan, Zhou, Ruyi, Bickel, Valentin, Ligeza, Gabriela, Miki, Takahiro, Kehl, Florian, Kolvenbach, Hendrik, Hutter, Marco
Publikováno v:
Science Robotics 2023 Vol. 8, Issue 80, eade9548
The interest in exploring planetary bodies for scientific investigation and in-situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots' inability to
Externí odkaz:
http://arxiv.org/abs/2307.10079
Autor:
Deas, Nicholas, Grieser, Jessi, Kleiner, Shana, Patton, Desmond, Turcan, Elsbeth, McKeown, Kathleen
We evaluate how well LLMs understand African American Language (AAL) in comparison to their performance on White Mainstream English (WME), the encouraged "standard" form of English taught in American classrooms. We measure LLM performance using autom
Externí odkaz:
http://arxiv.org/abs/2305.14291
Modern robotic systems are required to operate in challenging environments, which demand reliable localization under challenging conditions. LiDAR-based localization methods, such as the Iterative Closest Point (ICP) algorithm, can suffer in geometri
Externí odkaz:
http://arxiv.org/abs/2211.16335
Autor:
Turcan, Elsbeth, Wang, Shuai, Anubhai, Rishita, Bhattacharjee, Kasturi, Al-Onaizan, Yaser, Muresan, Smaranda
Detecting what emotions are expressed in text is a well-studied problem in natural language processing. However, research on finer grained emotion analysis such as what causes an emotion is still in its infancy. We present solutions that tackle both
Externí odkaz:
http://arxiv.org/abs/2106.09790
Autor:
Wan, David, Kedzie, Chris, Ladhak, Faisal, Turcan, Elsbeth, Galuščáková, Petra, Zotkina, Elena, Jiang, Zhengping, Bell, Peter, McKeown, Kathleen
Typical ASR systems segment the input audio into utterances using purely acoustic information, which may not resemble the sentence-like units that are expected by conventional machine translation (MT) systems for Spoken Language Translation. In this
Externí odkaz:
http://arxiv.org/abs/2104.07868