88 citations · 165 across the 15 of their papers we have counts for
15 papers
Designing a skilled soccer team for RoboCup: exploring skill-set-primitives through reinforcement learning
Miguel Abreu, Luis Paulo Reis, Nuno Lau
The RoboCup 3D Soccer Simulation League serves as a competitive platform for showcasing innovation in autonomous humanoid robot agents through simulated soccer matches. Our team, F…
Addressing imperfect symmetry: A novel symmetry-learning actor-critic extension
Miguel Abreu, Luis Paulo Reis, Nuno Lau
Symmetry, a fundamental concept to understand our environment, often oversimplifies reality from a mathematical perspective. Humans are a prime example, deviating from perfect symm…
FC Portugal 3D Simulation Team: Team Description Paper 2020
Nuno Lau, Luis Paulo Reis, David Simoes +3
The FC Portugal 3D team is developed upon the structure of our previous Simulation league 2D/3D teams and our standard platform league team. Our research concerning the robot low-l…
Q-Learning based system for path planning with unmanned aerial vehicles swarms in obstacle environments
Alejandro Puente-Castro, Daniel Rivero, Eurico Pedrosa +3
Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios whe…
Robust Biped Locomotion Using Deep Reinforcement Learning on Top of an Analytical Control Approach
Mohammadreza Kasaei, Miguel Abreu, Nuno Lau +2
This paper proposes a modular framework to generate robust biped locomotion using a tight coupling between an analytical walking approach and deep reinforcement learning. This fram…
A CPG-Based Agile and Versatile Locomotion Framework Using Proximal Symmetry Loss
Mohammadreza Kasaei, Miguel Abreu, Nuno Lau +2
Humanoid robots are made to resemble humans but their locomotion abilities are far from ours in terms of agility and versatility. When humans walk on complex terrains, or face exte…