5 papers · 1 filter
Actuator Reality Shaping for Zero-Shot Sim-to-Real Robot Learning
Satoshi Yamamori, Koji Ishihara, Kenjiro Minamikawa +4
Sim-to-real transfer in robot learning is often limited by discrepancies between the ideal actuator dynamics assumed during policy training and the nonlinear, hardware-dependent be…
DecompGrind: A Decomposition Framework for Robotic Grinding via Cutting-Surface Planning and Contact-Force Adaptation
Shunsuke Araki, Takumi Hachimine, Yuki Saito +3
Robotic grinding is widely used for shaping workpieces in manufacturing, but it remains difficult to automate this process efficiently. In particular, efficiently grinding workpiec…
Object-Centric Mobile Manipulation through SAM2-Guided Perception and Imitation Learning
Wang Zhicheng, Satoshi Yagi, Satoshi Yamamori +1
Imitation learning for mobile manipulation is a key challenge in the field of robotic manipulation. However, current mobile manipulation frameworks typically decouple navigation an…
Phase-Amplitude Reduction-Based Imitation Learning
Satoshi Yamamori, Jun Morimoto
In this study, we propose the use of the phase-amplitude reduction method to construct an imitation learning framework. Imitating human movement trajectories is recognized as a pro…
Goal-Conditioned Terminal Value Estimation for Real-time and Multi-task Model Predictive Control
Mitsuki Morita, Satoshi Yamamori, Satoshi Yagi +2
While MPC enables nonlinear feedback control by solving an optimal control problem at each timestep, the computational burden tends to be significantly large, making it difficult t…