1 code implementation • 23 Apr 2024 • Mateus G. Machado, João G. Melo, Cleber Zanchettin, Pedro H. M. Braga, Pedro V. Cunha, Edna N. S. Barros, Hansenclever F. Bassani
This work investigates the potential of Reinforcement Learning (RL) to tackle robot motion planning challenges in the dynamic RoboCup Small Size League (SSL).
no code implementations • 24 Jun 2021 • Ygor C. N. Sousa, Hansenclever F. Bassani
In contrast, this work introduces a topological semantic mapping method that uses deep visual features extracted by a CNN (GoogLeNet), from 2D images captured in multiple views of the environment as the robot operates, to create, through averages, consolidated representations of the visual features acquired in the regions covered by each topological node.
1 code implementation • 15 Jun 2021 • Felipe B. Martins, Mateus G. Machado, Hansenclever F. Bassani, Pedro H. M. Braga, Edna S. Barros
Reinforcement learning is an active research area with a vast number of applications in robotics, and the RoboCup competition is an interesting environment for studying and evaluating reinforcement learning methods.
1 code implementation • 23 Nov 2020 • Carlos H. C. Pena, Mateus G. Machado, Mariana S. Barros, José D. P. Silva, Lucas D. Maciel, Tsang Ing Ren, Edna N. S. Barros, Pedro H. M. Braga, Hansenclever F. Bassani
The IEEE Very Small Size Soccer (VSSS) is a robot soccer competition in which two teams of three small robots play against each other.
no code implementations • 18 Aug 2020 • Hansenclever F. Bassani, Renie A. Delgado, José Nilton de O. Lima Junior, Heitor R. Medeiros, Pedro H. M. Braga, Mateus G. Machado, Lucas H. C. Santos, Alain Tapp
This article introduces an open framework, called VSSS-RL, for studying Reinforcement Learning (RL) and sim-to-real in robot soccer, focusing on the IEEE Very Small Size Soccer (VSSS) league.
1 code implementation • 17 Jun 2020 • Pedro H. M. Braga, Heitor R. Medeiros, Hansenclever F. Bassani
The results show that Batch SS-SOM is a good option for semi-supervised classification and clustering.
no code implementations • 24 Mar 2020 • Hansenclever F. Bassani, Renie A. Delgado, Jose Nilton de O. Lima Junior, Heitor R. Medeiros, Pedro H. M. Braga, Alain Tapp
This work presents an application of Reinforcement Learning (RL) for the complete control of real soccer robots of the IEEE Very Small Size Soccer (VSSS), a traditional league in the Latin American Robotics Competition (LARC).
no code implementations • 15 Aug 2019 • Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever F. Bassani, Aluizio F. R. Araújo
In this paper, we propose the MOEA/D with Uniformly Randomly Adaptive Weights (MOEA/DURAW) which uses the Uniformly Randomly method as an approach to subproblems generation, allowing a flexible population size even when working with many objective problems.
no code implementations • 7 Aug 2019 • Raphael C. Brito, Hansenclever F. Bassani
Time Series Motif Discovery (TSMD) is defined as searching for patterns that are previously unknown and appear with a given frequency in time series.
no code implementations • 9 Jul 2019 • Ygor C. N. Sousa, Hansenclever F. Bassani
This paper introduces an incremental semantic mapping approach, with on-line unsupervised learning, based on Self-Organizing Maps (SOM) for robotic agents.
1 code implementation • 1 Jul 2019 • Pedro H. M. Braga, Hansenclever F. Bassani
There has been an increasing interest in semi-supervised learning in the recent years because of the great number of datasets with a large number of unlabeled data but only a few labeled samples.
1 code implementation • 1 Jul 2019 • Pedro H. M. Braga, Hansenclever F. Bassani
Also, it is important to develop methods that are easy to parameterize in a way that is robust to the different characteristics of the data at hand.
no code implementations • 20 May 2019 • Hansenclever F. Bassani, Aluizio F. R. Araujo
This article proposes a biologically inspired neurocomputational architecture which learns associations between words and referents in different contexts, considering evidence collected from the literature of Psycholinguistics and Neurolinguistics.