54 citations · 147 across the 10 of their papers we have counts for
3 papers · 1 filter
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…