activity
20242026
most citedFlightBench: Benchmarking Learning-based Methods for Ego-vision-based Quadrotors Navigation

1 citations · 1 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2026

AgilePE: Autonomous UAV Pursuit-Evasion via Self-Play Reinforcement Learning

Wenhao Tang, Tianyang Chen, Zhejun Cui +9

Autonomous pursuit-evasion is a fundamental challenge for Unmanned Aerial Vehicles (UAVs), requiring rapid decision-making under tightly coupled dynamics and continuously changing…

cs.RO2025

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…

cs.LG2025

Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance

Songsheng Wang, Rucheng Yu, Zhihang Yuan +4

Vision-Language-Action (VLA) models have made substantial progress by leveraging the robust capabilities of Visual Language Models (VLMs). However, VLMs' significant parameter size…

cs.LG2025

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…

cs.RO2025

Multi-Robot System for Cooperative Exploration in Unknown Environments: A Survey

Chuqi Wang, Chao Yu, Xin Xu +11

With the real need of field exploration in large-scale and extreme outdoor environments, cooperative exploration tasks have garnered increasing attention. This paper presents a com…

cs.LG2025

Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network

Jijia Liu, Feng Gao, Qingmin Liao +2

Reinforcement learning (RL) for continuous control often requires large amounts of online interaction data. Value-based RL methods can mitigate this burden by offering relatively h…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation

Weizheng Wang, Chao Yu, Yu Wang +1

Navigating in human-filled public spaces is a critical challenge for deploying autonomous robots in real-world environments. This paper introduces NaviDIFF, a novel Hamiltonian-con…

cs.RO2024★ 1 cited

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…

cs.RO2024

Localization matters too: How localization error affects UAV flight

Suquan Zhang, Yuanfan Xu, Shu'ang Yu +3

The maximum safe flight speed of a Unmanned Aerial Vehicle (UAV) is an important indicator for measuring its efficiency in completing various tasks. This indicator is influenced by…