From the 2 of 6 linked papers with an AI index.
6 papers
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
The paper introduces AeroAct, a world-action model that predicts quadrotor flight actions from egocentric video, proprioceptive data, and language commands, using a video diffusion…
Motubrain: An Advanced World Action Model for Robot Control
Motubrain Team, Chendong Xiang, Fan Bao +17
Motubrain is a unified world action model that jointly learns video and robot actions using a UniDiffuser and Mixture-of-Transformers architecture, enabling policy learning, world…
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…
DyMoDreamer: World Modeling with Dynamic Modulation
Boxuan Zhang, Runqing Wang, Wei Xiao +5
A critical bottleneck in deep reinforcement learning (DRL) is sample inefficiency, as training high-performance agents often demands extensive environmental interactions. Model-bas…
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…