1 citations · 1 across the 9 of their papers we have counts for
9 papers
NavCMPO: Critic-Guided MeanFlow Policy Optimization for Adaptive Navigation
Junjie An, Yi Wu, Xiao Liu +5
End-to-end diffusion-based policies have demonstrated strong performance in mapless visual navigation, but their iterative denoising process introduces substantial inference latenc…
SoftNav: Injecting 3D Scene Tokens into VLMs for Embodied Navigation
Yi Wu, Junjie An, Xiao Liu +6
In goal-directed embodied navigation, where an agent must locate a specified target in an unseen environment, 3D scene understanding and navigation reasoning must work in concert.…
D3P: Dynamic Denoising Diffusion Policy via Reinforcement Learning
Shu-Ang Yu, Feng Gao, Yi Wu +2
Diffusion policies excel at learning complex action distributions for robotic visuomotor tasks, yet their iterative denoising process poses a major bottleneck for real-time deploym…
What Can RL Bring to VLA Generalization? An Empirical Study
Jijia Liu, Feng Gao, Bingwen Wei +5
Large Vision-Language Action (VLA) models have shown significant potential for embodied AI. However, their predominant training via supervised fine-tuning (SFT) limits generalizati…
Fine-tuning Diffusion Policies with Backpropagation Through Diffusion Timesteps
Ningyuan Yang, Jiaxuan Gao, Feng Gao +2
Diffusion policies, widely adopted in decision-making scenarios such as robotics, gaming and autonomous driving, are capable of learning diverse skills from demonstration data due…
What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Study
Jiayu Chen, Chao Yu, Yuqing Xie +9
Executing precise and agile flight maneuvers is critical for quadrotors in various applications. Traditional quadrotor control approaches are limited by their reliance on flat traj…
Neural Internal Model Control: Learning a Robust Control Policy via Predictive Error Feedback
Feng Gao, Chao Yu, Yu Wang +1
Accurate motion control in the face of disturbances within complex environments remains a major challenge in robotics. Classical model-based approaches often struggle with nonlinea…
Multi-UAV Formation Control with Static and Dynamic Obstacle Avoidance via Reinforcement Learning
Yuqing Xie, Chao Yu, Hongzhi Zang +7
This paper tackles the challenging task of maintaining formation among multiple unmanned aerial vehicles (UAVs) while avoiding both static and dynamic obstacles during directed fli…
FlightBench: Benchmarking Learning-based Methods for Ego-vision-based Quadrotors Navigation
Shu-Ang Yu, Chao Yu, Feng Gao +2
Ego-vision-based navigation in cluttered environments is crucial for mobile systems, particularly agile quadrotors. While learning-based methods have shown promise recently, head-t…