Compensation for undefined behaviors during robot task execution by switching controllers depending on embedded dynamics in RNN

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

Robotic applications require both correct task performance and compensation for undefined behaviors. Although deep learning is a promising approach to perform complex tasks, the re…