no code implementations • 18 Jan 2024 • Koki Yamane, Sho Sakaino, Toshiaki Tsuji
However, these approaches face a critical challenge when processing data from multiple modalities, inadvertently ignoring data with a lower correlation to the desired output, especially when using short sampling periods.
no code implementations • 7 Dec 2021 • Yuya Nogi, Sho Sakaino, Toshiaki Tsuji
In this paper, we propose an external force estimation method based on the Mel spectrogram of the force obtained from a force sensor.
no code implementations • 22 Nov 2021 • Masahiro Aita, Keito Sugawara, Sho Sakaino, Toshiaki Tsuji
By combining two separately trained VAE models in a hierarchical structure, it is possible to generate trajectories with high reproducibility for both local and global features.
no code implementations • 11 Mar 2021 • Yuki Saigusa, Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji
In this paper, we propose a variable speed motion generation method for multiple motions.
Imitation Learning Robotics
no code implementations • 12 Nov 2020 • Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji
Owing to the structure and autoregressive learning of the proposed model, the proposed method can generate the desirable motion for successful tasks and have a high generalization ability for environmental changes.
no code implementations • 27 Feb 2020 • Masahide Oikawa, Kyo Kutsuzawa, Sho Sakaino, Toshiaki Tsuji
In this study, we propose a methodology that uses reinforcement learning (RL) to achieve high performance in robots for the execution of assembly tasks that require precise contact with objects without causing damage.