2 papers
cs.RO2024
Self-Supervised Learning of Grasping Arbitrary Objects On-the-Move
Takuya Kiyokawa, Eiki Nagata, Yoshihisa Tsurumine +2
Mobile grasping enhances manipulation efficiency by utilizing robots' mobility. This study aims to enable a commercial off-the-shelf robot for mobile grasping, requiring precise ti…
cs.RO2022
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…