Refine
Year of publication
- 2021 (1)
Document Type
Conference Type
- Konferenzartikel (1) (remove)
Language
- English (1)
Has Fulltext
- no (1)
Is part of the Bibliography
- yes (1)
Open Access
- Grün (1)
- Open Access (1)
This paper describes a thorough analysis of using PPO to learn kick behaviors with simulated NAO robots in the simspark environment. The analysis includes an investigation of the influence of PPO hyperparameters, network size, training setups and performance in real games. We believe to improve the state of the art mainly in four points: first, the kicks are learned with a toed version of the NAO robot, second, we improve the reliability with respect to kickable area and avoidance of falls, third, the kick can be parameterized with desired distance and direction as input to the deep network and fourth, the approach allows to integrate the learned behavior seamlessly into soccer games. The result is a significant improvement of the general level of play.