6 papers · 1 filter
Motus2: A Self-Evolving General World Model for Dexterous Manipulation
Hongzhe Bi, Zihao Zhou, Yihang Tang +16
General embodied agents should perceive, predict, act, evaluate, and improve within a unified system. World models have shown great promise in building such agents, yet existing mo…
FlowPilot: Real-Time World-Action Modeling for Agile UAV Navigation
Runqing Wang, Ding Yu, Pengyuan Min +6
We present FlowPilot, a compact world-action model for real-time onboard UAV navigation from depth. Unlike map-then-optimize pipelines that require local reconstruction or end-to-e…
AeroAct: Action-Centered World-Action Models for Language-Conditioned Quadrotor Flight
Xinhong Zhang, Qiyuan Zhu, Yubo Huang +8
Language-conditioned quadrotor flight requires a policy to ground semantic goals, anticipate the visual consequences of ego-motion, and output control references that remain smooth…
MAD: Mapping-Aware World Models for Agile Quadrotor Flight
Xinhong Zhang, Runqing Wang, Yunfan Ren +6
Agile quadrotor flight in cluttered scenes requires more than a reactive mapping from a depth image to a control command: the vehicle must remember which regions have been observed…
Motubrain: An Advanced World Action Model for Robot Control
Motubrain Team, Chendong Xiang, Fan Bao +17
Vision-Language-Action (VLA) models generalize semantically well but often lack fine-grained modeling of world dynamics. We present Motubrain, a unified World Action Model that joi…
DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning
Xinhong Zhang, Runqing Wang, Yunfan Ren +4
This letter introduces DiffAero, a lightweight, GPU-accelerated, and fully differentiable simulation framework designed for efficient quadrotor control policy learning. DiffAero su…