UruBots 自律走行カーへの挑戦：FIRA 2025 Proチーム記述論文
UruBots Autonomous Cars Challenge Pro Team Description Paper for FIRA 2025
小型RCカーサイズの自律走行車を開発し、カメラ画像をCNNで処理してステアリングとスロットルを制御、障害物を避けながらトラックを30秒以内で完走した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Pablo Moraes, Mónica Rodríguez, Sebastian Barcelona, Angel Da Silva, Santiago Fernandez, Hiago Sodre, Igor Nunes, Bruna Guterres, Ricardo Grando
分類: cs.RO, cs.SY, eess.IV, eess.SY
原文アブストラクト
This paper describes the development of an autonomous car by the UruBots team for the 2025 FIRA Autonomous Cars Challenge (Pro). The project involves constructing a compact electric vehicle, approximately the size of an RC car, capable of autonomous navigation through different tracks. The design incorporates mechanical and electronic components and machine learning algorithms that enable the vehicle to make real-time navigation decisions based on visual input from a camera. We use deep learning models to process camera images and control vehicle movements. Using a dataset of over ten thousand images, we trained a Convolutional Neural Network (CNN) to drive the vehicle effectively, through two outputs, steering and throttle. The car completed the track in under 30 seconds, achieving a pace of approximately 0.4 meters per second while avoiding obstacles.
