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Generating Synthetic Training Images for Deep Reinforcement Learning of a Mobile Robot |
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| รหัสดีโอไอ | |
| Creator | Sumeth Yuenyong |
| Title | Generating Synthetic Training Images for Deep Reinforcement Learning of a Mobile Robot |
| Contributor | Qu Jian |
| Publisher | Sirindhorn International Institute of Technology, Bangkadi Campus (SIIT-BKD) |
| Publication Year | 2560 |
| Journal Title | Journal of Intelligent Informatics and Smart Technology |
| Journal Vol. | 2 |
| Page no. | 1-4 |
| Keyword | variational autoencoder, deep reinforcement learning, machine learning |
| URL Website | https://ph05.tci-thaijo.org/index.php/JIIST |
| Website title | Journal of Intelligent Informatics and Smart Technology |
| ISSN | 2586-9167 |
| Abstract | This paper proposes the use of variational autoencoder (VAE) to generate synthetic training images for deep reinforcement learning of a mobile robot. Deep reinforcement learning typically requires millions of interactions with the real world in order to learn good control policies, which is impractical for robotic tasks. Using synthetic images generated by a VAE, one may be able to reduce the number of interactions by running a deep reinforcement learning algorithm off these images, instead of real ones captured by the camera. Our experiment shows, for this particular task, that the VAE can generate synthetic images which are almost non-discernible from those obtained by direct reconstruction of real images. |
