62 citations · 165 across the 28 of their papers we have counts for
5 papers · 1 filter
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…
Generation Drawing/Grinding Trajectoy Based on Hierarchical CVAE
Masahiro Aita, Keito Sugawara, Sho Sakaino +1
In this study, we propose a method to model the local and global features of the drawing/grinding trajectory with hierarchical Variational Autoencoders (VAEs). By combining two sep…
A New Autoregressive Neural Network Model with Command Compensation for Imitation Learning Based on Bilateral Control
Kazuki Hayashi, Ayumu Sasagawa, Sho Sakaino +1
In the near future, robots are expected to work with humans or operate alone and may replace human workers in various fields such as homes and factories. In a previous study, we pr…
Imitation learning for variable speed motion generation over multiple actions
Yuki Saigusa, Ayumu Sasagawa, Sho Sakaino +1
Robotic motion generation methods using machine learning have been studied in recent years. Bilateral control-based imitation learning can imitate human motions using force informa…
Imitation Learning for Variable Speed Contact Motion for Operation up to Control Bandwidth
Sho Sakaino, Kazuki Fujimoto, Yuki Saigusa +1
The generation of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based mo…