Observation Denoising in CYRUS Soccer Simulation 2D Team For RoboCup 2023
This addresses noise in sensor data for a specific RoboCup simulation team, making it incremental.
The paper tackles the problem of observation noise in the RoboCup Soccer Simulation 2D League by proposing a denoising method using LSTM and DNN, resulting in the CYRUS team winning the RoboCup 2021 championship.
The RoboCup competitions hold various leagues, and the Soccer Simulation 2D League is a major one among them. Soccer Simulation 2D (SS2D) match involves two teams, including 11 players and a coach, competing against each other. The players can only communicate with the Soccer Simulation Server during the game. This paper presents the latest research of the CYRUS soccer simulation 2D team, the champion of RoboCup 2021. We will explain our denoising idea powered by long short-term memory networks (LSTM) and deep neural networks (DNN). The CYRUS team uses the CYRUS2D base code that was developed based on the Helios and Gliders bases.