32 citations · 38 across the 3 of their papers we have counts for
9 papers
An Independently Learnable Hierarchical Model for Bilateral Control-Based Imitation Learning Applications
Kazuki Hayashi, Sho Sakaino, Toshiaki Tsuji
Recently, motion generation by machine learning has been actively researched to automate various tasks. Imitation learning is one such method that learns motions from data collecte…
Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning
Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji
Robots that can execute various tasks automatically on behalf of humans are becoming an increasingly important focus of research in the field of robotics. Imitation learning has be…
Assembly robots with optimized control stiffness through reinforcement learning
Masahide Oikawa, Kyo Kutsuzawa, Sho Sakaino +1
There is an increased demand for task automation in robots. Contact-rich tasks, wherein multiple contact transitions occur in a series of operations, are extensively being studied…
Design of Resonance Ratio Control with Relative Position Information for Two-inertia System
Kenta Araake, Sho Sakaino, Toshiaki Tsuji
Two-inertia systems are prone to resonance vibrations that degrade their control performances. These unwanted vibrations can be effectively suppressed by control methods based on a…
Time Series Motion Generation Considering Long Short-Term Motion
Kazuki Fujimoto, Sho Sakaino, Toshiaki Tsuji
Various adaptive abilities are required for robots interacting with humans in daily life. It is difficult to design adaptive algorithms manually; however, by using end-to-end machi…
Imitation Learning Based on Bilateral Control for Human-Robot Cooperation
Ayumu Sasagawa, Kazuki Fujimoto, Sho Sakaino +1
Robots are required to autonomously respond to changing situations. Imitation learning is a promising candidate for achieving generalization performance, and extensive results have…