62 citations · 162 across the 32 of their papers we have counts for
6 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…
Bilateral Control-Based Imitation Learning for Velocity-Controlled Robot
Sho Sakaino
Machine learning is now playing important role in robotic object manipulation. In addition, force control is necessary for manipulating various objects to achieve robustness agains…
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…