9 papers
Self-Supervised Anchoring of Fingertip Sensing to Proprioception and Proactive Actions for Robot Imitation Learning
Tomohiro Motoda, Masaki Murooka, Keisuke Shirai +6
Robotic imitation learning often relies on external cameras, yet local interaction cues such as object proximity, contact onset, and grasp state are difficult to observe near the f…
Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining
Shogo Iwakata, Tomohiro Motoda, Ryosuke Yamada +8
Applying an imitation learning policy to a new manipulation task usually requires collecting new demonstrations and retraining the model, which makes sample efficiency a practical…
Non-Prehensile Throwing: A Reinforcement Learning Perspective
Abdullah Mustafa, Ryo Hanai, Ixchel G. Ramirez-Alpizar +4
Robotic throwing enables fast object transport and extends a robot's reachable workspace beyond traditional pick-and-place. While prehensile (grasp-based) throwing works well for g…
The Embodiment Gap in Robot Foundation Models
Yukiyasu Domae, Keisuke Shirai, Hanbit Oh +7
Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, and broader benchmarks should…
GuidedAttention: Interpretable and Correctable Visual Attention for OOD-Robust Robot Manipulation via Imitation Learning
Masaki Murooka, Ryoichi Nakajo, Keisuke Shirai +4
End-to-end visuomotor policies provide little opportunity for humans to understand or correct the policy's visual attention. We propose GuidedAttention, a visuomotor imitation lear…
RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments
Masaki Murooka, Tomohiro Motoda, Ryoichi Nakajo +5
We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the entire imitation learning pipel…