An Open Source Vision Pipeline Approach for RoboCup Humanoid Soccer

Author:

Fiedler Niklas,Brandt Hendrik,Gutsche Jan,Vahl Florian,Hagge Jonas,Bestmann Marc

Publisher

Springer International Publishing

Reference22 articles.

1. Allali, J., Gondry, L., Hofer, L., Laborde-Zubieta, P., Ly, O., et al.: Rhoban football club - team description paper. Technical report, CNRS, LaBRI, University of Bordeaux and Bordeaux INP (2019)

2. Baltes, J., Missoura, M., Seifert, D., Sadeghnejad, S.: Robocup soccer humanoid league. Technical report (2013)

3. Barry, D., Curtis-Black, A., Keijsers, M., Munir, S., Young, M.: Electric sheep team description paper. Technical report, University of Canterbury, Christchurch, New Zealand (2019)

4. Bestmann, M., et al.: Hamburg bit-bots and wf wolves team description for RoboCup 2019 humanoid KidSize. Technical report, Universität Hamburg, Germany and Ostfalia University of Applied Sciences, Wolfenbüttel, Germany (2019)

5. Bestmann, M., Hendrich, N., Wasserfall, F.: ROS for humanoid soccer robots (2017)

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1. The human in the loop Perspectives and challenges for RoboCup 2050;Autonomous Robots;2024-05

2. Applying Monocular Depth Estimation in RoboCup Soccer;2022 IEEE International Conference on Robotics and Biomimetics (ROBIO);2022-12-05

3. Soccer Field Boundary Detection Using Convolutional Neural Networks;Lecture Notes in Computer Science;2022

4. TORSO-21 Dataset: Typical Objects in RoboCup Soccer 2021;Lecture Notes in Computer Science;2022

5. Shotifier: A Binary Shot Conversion Classifier Pipeline for Football Forwards;2021 IEEE International Conference on Big Data and Smart Computing (BigComp);2021-01

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