1 citations · 2 across the 12 of their papers we have counts for
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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…
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…
Robust Offline Imitation Learning Through State-level Trajectory Stitching
Shuze Wang, Yunpeng Mei, Hongjie Cao +4
Imitation learning (IL) has proven effective for enabling robots to acquire visuomotor skills through expert demonstrations. However, traditional IL methods are limited by their re…
Time-optimal Flight in Cluttered Environments via Safe Reinforcement Learning
Wei Xiao, Zhaohan Feng, Ziyu Zhou +3
This paper addresses the problem of guiding a quadrotor through a predefined sequence of waypoints in cluttered environments, aiming to minimize the flight time while avoiding coll…
Learning Hybrid Policies for MPC with Application to Drone Flight in Unknown Dynamic Environments
Zhaohan Feng, Jie Chen, Wei Xiao +3
In recent years, drones have found increased applications in a wide array of real-world tasks. Model predictive control (MPC) has emerged as a practical method for drone flight con…