4 papers
Variable-Frequency Imitation Learning for Variable-Speed Motion
Nozomu Masuya, Sho Sakaino, Toshiaki Tsuji
Conventional methods of imitation learning for variable-speed motion have difficulty extrapolating speeds because they rely on learning models running at a constant sampling freque…
Error-Feedback Model for Output Correction in Bilateral Control-Based Imitation Learning
Hiroshi Sato, Masashi Konosu, Sho Sakaino +1
In recent years, imitation learning using neural networks has enabled robots to perform flexible tasks. However, since neural networks operate in a feedforward structure, they do n…
Imitation Learning Inputting Image Feature to Each Layer of Neural Network
Koki Yamane, Sho Sakaino, Toshiaki Tsuji
Imitation learning enables robots to learn and replicate human behavior from training data. Recent advances in machine learning enable end-to-end learning approaches that directly…
Force control of grinding process based on frequency analysis
Yuya Nogi, Sho Sakaino, Toshiaki Tsuji
Hysteresis-induced drift is a major issue in the detection of force induced during grinding and cutting operations. In this paper, we propose an external force estimation method ba…