rSoccer: A Framework for Studying Reinforcement Learning in Small and Very Small Size Robot Soccer

06/15/2021
by   Felipe B. Martins, et al.
0

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. A known difficulty in applying reinforcement learning to robotics is the high number of experience samples required, being the use of simulated environments for training the agents followed by transfer learning to real-world (sim-to-real) a viable path. This article introduces an open-source simulator for the IEEE Very Small Size Soccer and the Small Size League optimized for reinforcement learning experiments. We also propose a framework for creating OpenAI Gym environments with a set of benchmarks tasks for evaluating single-agent and multi-agent robot soccer skills. We then demonstrate the learning capabilities of two state-of-the-art reinforcement learning methods as well as their limitations in certain scenarios introduced in this framework. We believe this will make it easier for more teams to compete in these categories using end-to-end reinforcement learning approaches and further develop this research area.

READ FULL TEXT
research
08/18/2020

A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer

This article introduces an open framework, called VSSS-RL, for studying ...
research
07/25/2019

Google Research Football: A Novel Reinforcement Learning Environment

Recent progress in the field of reinforcement learning has been accelera...
research
01/11/2022

Active Reinforcement Learning – A Roadmap Towards Curious Classifier Systems for Self-Adaptation

Intelligent systems have the ability to improve their behaviour over tim...
research
11/23/2020

An analysis of Reinforcement Learning applied to Coach task in IEEE Very Small Size Soccer

The IEEE Very Small Size Soccer (VSSS) is a robot soccer competition in ...
research
12/08/2020

NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environments

Robot navigation is a task where reinforcement learning approaches are s...
research
06/04/2019

Autonomous Reinforcement Learning of Multiple Interrelated Tasks

Autonomous multiple tasks learning is a fundamental capability to develo...
research
07/28/2022

RangL: A Reinforcement Learning Competition Platform

The RangL project hosted by The Alan Turing Institute aims to encourage ...

Please sign up or login with your details

Forgot password? Click here to reset