Zobrazeno 1 - 10
of 381
pro vyhledávání: '"Guerra Rodrigo"'
Autor:
Grando, Ricardo B., Steinmetz, Raul, Kich, Victor A., Kolling, Alisson H., Furik, Pablo M., de Jesus, Junior C., Guterres, Bruna V., Gamarra, Daniel T., Guerra, Rodrigo S., Drews-Jr, Paulo L. J.
Deep Reinforcement Learning (DRL) has emerged as a promising approach to enhancing motion control and decision-making through a wide range of robotic applications. While prior research has demonstrated the efficacy of DRL algorithms in facilitating a
Externí odkaz:
http://arxiv.org/abs/2406.01952
Autor:
Grando, Ricardo B., de Jesus, Junior C., Kich, Victor A., Kolling, Alisson H., Guerra, Rodrigo S., Drews-Jr, Paulo L. J.
Deep Reinforcement Learning (Deep-RL) techniques for motion control have been continuously used to deal with decision-making problems for a wide variety of robots. Previous works showed that Deep-RL can be applied to perform mapless navigation, inclu
Externí odkaz:
http://arxiv.org/abs/2308.09811
The field of robotics, and more especially humanoid robotics, has several established competitions with research oriented goals in mind. Challenging the robots in a handful of tasks, these competitions provide a way to gauge the state of the art in r
Externí odkaz:
http://arxiv.org/abs/2212.11071
Autor:
Bottega, Jair A., Kich, Victor A., Kolling, Alisson H., Dyonisio, Jardel D. S., Corçaque, Pedro L., Guerra, Rodrigo da S., Gamarra, Daniel F. T.
Human-robot interaction (HRI) is essential to the widespread use of robots in daily life. Robots will eventually be able to carry out a variety of duties in human civilization through effective social interaction. Creating straightforward and underst
Externí odkaz:
http://arxiv.org/abs/2209.13509
Autor:
Grando, Ricardo B., de Jesus, Junior C., Kich, Victor A., Kolling, Alisson H., Guerra, Rodrigo S., Drews-Jr, Paulo L. J.
Previous works showed that Deep-RL can be applied to perform mapless navigation, including the medium transition of Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs). This paper presents new approaches based on the state-of-the-art actor-critic alg
Externí odkaz:
http://arxiv.org/abs/2209.06332
Autor:
Grando, Ricardo B., de Jesus, Junior C., Kich, Victor A., Kolling, Alisson H., Guerra, Rodrigo S., Drews-Jr, Paulo L. J.
Deterministic and Stochastic techniques in Deep Reinforcement Learning (Deep-RL) have become a promising solution to improve motion control and the decision-making tasks for a wide variety of robots. Previous works showed that these Deep-RL algorithm
Externí odkaz:
http://arxiv.org/abs/2209.06328
Autor:
de Jesus, Junior Costa, Kich, Victor Augusto, Kolling, Alisson Henrique, Grando, Ricardo Bedin, Guerra, Rodrigo da Silva, Drews Jr, Paulo Lilles Jorge
Reinforcement Learning (RL) has presented an impressive performance in video games through raw pixel imaging and continuous control tasks. However, RL performs poorly with high-dimensional observations such as raw pixel images. It is generally accept
Externí odkaz:
http://arxiv.org/abs/2206.15211
Publikováno v:
Benchmarking: An International Journal, 2023, Vol. 31, Issue 2, pp. 590-610.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/BIJ-06-2022-0404
Autor:
Kich, Victor Augusto, de Jesus, Junior Costa, Grando, Ricardo Bedin, Kolling, Alisson Henrique, Heisler, Gabriel Vinícius, Guerra, Rodrigo da Silva
Deep Reinforcement Learning (DRL) has produced great achievements since it was proposed, including the possibility of processing raw vision input data. However, training an agent to perform tasks based on image feedback remains a challenge. It requir
Externí odkaz:
http://arxiv.org/abs/2204.11370
Autor:
Bom, Marlone H.H., Ceolin, Daiane, Kochhann, Karlos G.D., Guerra, Rodrigo Do Monte, Krahl, Guilherme, Patarroyo, German, Pacheco, Mírian L.F.A., Oliveira, Lucas V., Musso, Telma, Concheyro, Andrea, Fauth, Gerson
Publikováno v:
In Marine Micropaleontology April 2024 188