25 citations · 67 across the 8 of their papers we have counts for
8 papers
ROS2Learn: a reinforcement learning framework for ROS 2
Yue Leire Erro Nuin, Nestor Gonzalez Lopez, Elias Barba Moral +4
We propose a novel framework for Deep Reinforcement Learning (DRL) in modular robotics to train a robot directly from joint states, using traditional robotic tools. We use an state…
gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebo
Nestor Gonzalez Lopez, Yue Leire Erro Nuin, Elias Barba Moral +4
This paper presents an upgraded, real world application oriented version of gym-gazebo, the Robot Operating System (ROS) and Gazebo based Reinforcement Learning (RL) toolkit, which…
Robot_gym: accelerated robot training through simulation in the cloud with ROS and Gazebo
Víctor Mayoral Vilches, Alejandro Hernández Cordero, Asier Bilbao Calvo +2
Rather than programming, training allows robots to achieve behaviors that generalize better and are capable to respond to real-world needs. However, such training requires a big am…
An information model for modular robots: the Hardware Robot Information Model (HRIM)
Irati Zamalloa, Iñigo Muguruza, Alejandro Hernández +2
Today's landscape of robotics is dominated by vertical integration where single vendors develop the final product leading to slow progress, expensive products and customer lock-in.…
Hierarchical Learning for Modular Robots
Risto Kojcev, Nora Etxezarreta, Alejandro Hernández +1
We argue that hierarchical methods can become the key for modular robots achieving reconfigurability. We present a hierarchical approach for modular robots that allows a robot to s…
Towards self-adaptable robots: from programming to training machines
Víctor Mayoral, Risto Kojcev, Nora Etxezarreta +2
We argue that hardware modularity plays a key role in the convergence of Robotics and Artificial Intelligence (AI). We introduce a new approach for building robots that leads to mo…
Evaluation of Deep Reinforcement Learning Methods for Modular Robots
Risto Kojcev, Nora Etxezarreta, Alejandro Hernández +1
We propose a novel framework for Deep Reinforcement Learning (DRL) in modular robotics using traditional robotic tools that extend state-of-the-art DRL implementations and provide…
Dissecting Robotics - historical overview and future perspectives
Irati Zamalloa, Risto Kojcev, Alejandro Hernández +4
Robotics is called to be the next technological revolution and estimations indicate that it will trigger the fourth industrial revolution. This article presents a review of some of…