4 papers · 1 filter
ViSA: Visited-State Augmentation for Generalized Goal-Space Contrastive Reinforcement Learning
Issa Nakamura, Tomoya Yamanokuchi, Yuki Kadokawa +5
Goal-Conditioned Reinforcement Learning (GCRL) is a framework for learning a policy that can reach arbitrarily given goals. In particular, Contrastive Reinforcement Learning (CRL)…
DISF: Disentangled Iterative Surface Fitting for Contact-stable Grasp Planning with Grasp Pose Alignment to the Object Center of Mass
Tomoya Yamanokuchi, Alberto Bacchin, Emilio Olivastri +3
In this work, we address the limitation of surface fitting-based grasp planning algorithm, which primarily focuses on geometric alignment between the gripper and object surface whi…
Disentangled Iterative Surface Fitting for Contact-stable Grasp Planning
Tomoya Yamanokuchi, Alberto Bacchin, Emilio Olivastri +2
In this work, we address the limitation of surface fitting-based grasp planning algorithm, which primarily focuses on geometric alignment between the gripper and object surface whi…
Randomized-to-Canonical Model Predictive Control for Real-world Visual Robotic Manipulation
Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine +3
Many works have recently explored Sim-to-real transferable visual model predictive control (MPC). However, such works are limited to one-shot transfer, where real-world data must b…