Zobrazeno 1 - 10
of 3 786
pro vyhledávání: '"A. Suriani"'
Autor:
Argenziano, Francesco, Brienza, Michele, Suriani, Vincenzo, Nardi, Daniele, Bloisi, Domenico D.
Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a standardized mapping between h
Externí odkaz:
http://arxiv.org/abs/2408.17379
Autor:
Brienza, Michele, Argenziano, Francesco, Suriani, Vincenzo, Bloisi, Domenico D., Nardi, Daniele
Large Language Models (LLMs) and Visual Language Models (VLMs) are attracting increasing interest due to their improving performance and applications across various domains and tasks. However, LLMs and VLMs can produce erroneous results, especially w
Externí odkaz:
http://arxiv.org/abs/2408.05478
Publikováno v:
Crop Protection, Volume 184, October 2024, 106848
The use of deep learning methods for precision farming is gaining increasing interest. However, collecting training data in this application field is particularly challenging and costly due to the need of acquiring information during the different gr
Externí odkaz:
http://arxiv.org/abs/2407.14119
Autor:
Brienza, Michele, Musumeci, Emanuele, Suriani, Vincenzo, Affinita, Daniele, Pennisi, Andrea, Nardi, Daniele, Bloisi, Domenico Daniele
The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup offers the chance to deploy robots in one of those scenarios, a human-s
Externí odkaz:
http://arxiv.org/abs/2406.18285
Publikováno v:
Lecture Notes in Computer Science ((LNAI,volume 14140)) Included in the following conference series: Robot World Cup RoboCup 2023: Robot World Cup XXVI
Robots playing soccer often rely on hard-coded behaviors that struggle to generalize when the game environment change. In this paper, we propose a temporal logic based approach that allows robots' behaviors and goals to adapt to the semantics of the
Externí odkaz:
http://arxiv.org/abs/2405.12628
Autor:
Musumeci, Emanuele, Brienza, Michele, Suriani, Vincenzo, Nardi, Daniele, Bloisi, Domenico Daniele
In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex and diverse. This complexity arises from the need to handle a wide ra
Externí odkaz:
http://arxiv.org/abs/2402.14871
Autor:
Affinita, Daniele, Volpi, Flavio, Spagnoli, Valerio, Suriani, Vincenzo, Nardi, Daniele, Bloisi, Domenico D.
RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soccer champion team by the year 2050. To achieve this goal, autonomous h
Externí odkaz:
http://arxiv.org/abs/2401.15026
Enriching the robot representation of the operational environment is a challenging task that aims at bridging the gap between low-level sensor readings and high-level semantic understanding. Having a rich representation often requires computationally
Externí odkaz:
http://arxiv.org/abs/2309.12692
Autor:
Suriani, Vincenzo, Nardi, Daniele
In the last years, robots are moving out of research laboratories to enter everyday life. Competitions aiming at benchmarking the capabilities of a robot in everyday scenarios are useful to make a step forward in this path. In fact, they foster the d
Externí odkaz:
http://arxiv.org/abs/2303.12492
Autor:
Fauziyah Harahap, Rehlitna Fransiska Sitepu, Syahmi Edi, Cicik Suriani, Abdul Hakim Daulae, Mansur As, Didi Febrian, Sitti Subaedah
Publikováno v:
Jurnal Biologi Udayana, Vol 28, Iss 1, Pp 158-169 (2024)
Penelitian ini bertujuan untuk mengetahui interaksi perlakuan BAP dan ekstrak jagung manis yang berpengaruh dalam membentuk tunas sebagai upaya perbanyakan anggrek Dendrobium sp. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) faktorial denga
Externí odkaz:
https://doaj.org/article/ca06e6e9c8bb4812b2748e27c5f6f060
