21 citations · 31 across the 18 of their papers we have counts for
26 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…
Online Material Estimation for Conditioned Diffusion Policy in Shaping Deformable Linear Objects
Ryunosuke Yamada, Tomohiro Motoda, Yukiyasu Domae +1
Shape control of deformable linear objects (DLOs) is challenging for imitation learning because deformation behavior varies with material properties such as stiffness and elasticit…
ARTiS: An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Disassembly Applications
Roman Mykhailyshyn, Yukiyasu Domae, Kensuke Harada
Grasping and holding tools while using them presents a considerable challenge not only for robots but also for humans. Such a challenge is particularly noticeable in processes invo…
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…
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…
ORPA: Online Residual Policy Adaptation for Robot Manipulation Control with Human Feedback
Muhammad A. Muttaqien, Tomohiro Motoda, Ryo Hanai +1
Robotic manipulation policies trained via imitation learning, such as Action Chunking with Transformers (ACT), can achieve strong performance under ideal conditions but often remai…