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Jason Chen

2 accepted papers

2026

ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation

ICRA 2026poster

Training robust bimanual manipulation policies via imitation learning requires demonstration data with broad coverage over robot poses, contacts, and scene contexts. However, collecting diverse and precise real-world demonstrations is costly and time-consuming, which hinders scalability. Prior works…

2025

D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation

CoRL 2025poster

Learning bimanual manipulation is challenging due to its high dimensionality and tight coordination required between two arms. Eye-in-hand imitation learning, which uses wrist-mounted cameras, simplifies perception by focusing on task-relevant views. However, collecting diverse demonstrations remain…

Cited by 0SourcecodeScholar