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Ruichen Yang

4 accepted papers

2026

CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots

ICRA 2026poster

For effective deployment in real-world environments, humanoid robots must autonomously navigate a diverse range of complex terrains with abrupt transitions. While the Vanilla mixture of experts (MoE) framework is theoretically capable of modeling diverse terrain features, in practice, the gating net…

2026

Drive in Corridors: Enhancing the Safety of End-To-End Autonomous Driving Via Corridor Learning and Planning

ICRA 2026poster

Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints.…

2026

LAOF: Robust Latent Action Learning with Optical Flow Constraints

CVPR 2026

Learning latent actions from large-scale videos is crucial for the pre-training of scalable embodied foundation models, yet existing methods often struggle with action-irrelevant distractors. Although incorporating action supervision can alleviate these distractions, its effectiveness is restricted

Cited by 0SourcecodeScholar
2025

Drive in Corridors: Enhancing the Safety of End-to-End Autonomous Driving via Corridor Learning and Planning

RA-L 2025

Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints.

Cited by 3SourcecodeScholar