51 citations · 91 across the 28 of their papers we have counts for
4 papers · 1 filter
Disentangling Patterns and Transformations from One Sequence of Images with Shape-invariant Lie Group Transformer
T. Takada, W. Shimaya, Y. Ohmura +1
An effective way to model the complex real world is to view the world as a composition of basic components of objects and transformations. Although humans through development under…
Goal-conditioned dual-action imitation learning for dexterous dual-arm robot manipulation
Heecheol Kim, Yoshiyuki Ohmura, Yasuo Kuniyoshi
Long-horizon dexterous robot manipulation of deformable objects, such as banana peeling, is a problematic task because of the difficulties in object modeling and a lack of knowledg…
Memory-based gaze prediction in deep imitation learning for robot manipulation
Heecheol Kim, Yoshiyuki Ohmura, Yasuo Kuniyoshi
Deep imitation learning is a promising approach that does not require hard-coded control rules in autonomous robot manipulation. The current applications of deep imitation learning…
Training Robots without Robots: Deep Imitation Learning for Master-to-Robot Policy Transfer
Heecheol Kim, Yoshiyuki Ohmura, Akihiko Nagakubo +1
Deep imitation learning is promising for robot manipulation because it only requires demonstration samples. In this study, deep imitation learning is applied to tasks that require…