5 papers · 1 filter
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…
Peg-in-Bench: A Modular Benchmark for High-Precision Robotic Insertion
Yosel Delgado, José G. Buenaventura-Carreón, Floris Erich +4
High-precision insertion remains a fundamental challenge in robotic manipulation due to the strict alignment requirements and contact-rich interactions involved. Although peg-in-ho…
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…
YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale
Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi +16
We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data collection for bimanual dexterous ma…
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…