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20242026
most citedVision-Proprioception Fusion with Mamba2 in End-to-End Reinforcement Learning for Motion Control

1 citations · 3 across the 13 of their papers we have counts for

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cs.RO2026

Average-Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning

Yinuo Wang, Gavin Tao, Yuze Liu +1

Underwater vehicles operate from a fixed onboard energy budget that propulsion rapidly depletes, so a controller that completes its task while drawing less thruster power directly…

cs.RO2026

Factor-Aware Mixture-of-Experts with Pretrained Encoder for Combinatorial Generalization

Feihong Zhang, Guojian Zhan, Zeyu He +8

The integration of pretrained encoders with diffusion policies has become a dominant paradigm for visual robotic manipulation. However, it still struggles to generalize across comp…

cs.RO2026

HuMam: Humanoid Motion Control via End-to-End Deep Reinforcement Learning with Mamba

Yinuo Wang, Yuanyang Qi, Jinzhao Zhou +2

End-to-end reinforcement learning (RL) for humanoid locomotion is appealing for its compact perception-action mapping, yet practical policies often suffer from training instability…

cs.RO20261 cited

Vision-Proprioception Fusion with Mamba2 in End-to-End Reinforcement Learning for Motion Control

Xiaowen Tao, Yinuo Wang, Jinzhao Zhou

End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for different robots and tasks…

cs.RO2025

LocoMamba: Vision-Driven Locomotion via End-to-End Deep Reinforcement Learning with Mamba

Yinuo Wang, Gavin Tao

We introduce LocoMamba, a vision-driven cross-modal DRL framework built on selective state-space models, specifically leveraging Mamba, that achieves near-linear-time sequence mode…