DeepAI AI Chat
Log In Sign Up

RoboCupSimData: A RoboCup soccer research dataset

11/06/2017
by   Olivia Michael, et al.
Western Sydney University
0

RoboCup is an international scientific robot competition in which teams of multiple robots compete against each other. Its different leagues provide many sources of robotics data, that can be used for further analysis and application of machine learning. This paper describes a large dataset from games of some of the top teams (from 2016 and 2017) in RoboCup Soccer Simulation League (2D), where teams of 11 robots (agents) compete against each other. Overall, we used 10 different teams to play each other, resulting in 45 unique pairings. For each pairing, we ran 25 matches (of 10mins), leading to 1125 matches or more than 180 hours of game play. The generated CSV files are 17GB of data (zipped), or 229GB (unzipped). The dataset is unique in the sense that it contains both the ground truth data (global, complete, noise-free information of all objects on the field), as well as the noisy, local and incomplete percepts of each robot. These data are made available as CSV files, as well as in the original soccer simulator formats.

READ FULL TEXT

page 1

page 2

page 3

page 4

10/12/2018

Estimating Robot Strengths with Application to Selection of Alliance Members in FIRST Robotics Competitions

Since the inception of the FIRST Robotics Competition and its special pl...
09/20/2022

Deep Q-Network for AI Soccer

Reinforcement learning has shown an outstanding performance in the appli...
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 ...
05/06/2022

Encouraging Human Interaction with Robot Teams: Legible and Fair Subtask Allocations

Recent works explore collaboration between humans and teams of robots. T...
02/02/2019

RoboCup@Home: Summarizing achievements in over eleven years of competition

Scientific competitions are important in robotics because they foster kn...
08/22/2022

Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The BARN Challenge at ICRA 2022

The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at...
06/07/2019

A Naive Bayes Approach for NFL Passing Evaluation using Tracking Data Extracted from Images

The NFL collects detailed tracking data capturing the location of all pl...