works on

From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

cs.CV2026

LiteMVS: Efficient Multi-View Stereo with Foundation Distillation and Expert Aggregation

Tianbao Zhang, Zeyu Liu, Shuyu Wu +4

Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods primarily rely on geometric cor…

cs.RO2026

Learning Agile Navigation in Crowded Environments for Quadruped Robots

Shuyu Wu, Zeyu Liu, Tianbao Zhang +6

The paper introduces VOP-Nav, a system that blends Velocity Obstacle theory with end‑to‑end learning to enable quadruped robots to navigate safely and quickly through crowded, dyna…

cs.RO2026

Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation

Fanxing Li, Shengyang Wang, Yuxiang Huang +5

Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory, existing approaches both on…

cs.RO2026

E2E-Fly: An Integrated Training-to-Deployment System for End-to-End Quadrotor Autonomy

Fangyu Sun, Fanxing Li, Linzuo Zhang +5

Training and transferring learning-based policies for quadrotors from simulation to reality remains challenging due to inefficient visual rendering, physical modeling inaccuracies,…

cs.RO2026

VisFly-Lab: Unified Differentiable Framework for First-Order Reinforcement Learning of Quadrotor Control

Fanxing Li, Fangyu Sun, Tianbao Zhang +5

First-order reinforcement learning with differentiable simulation is promising for quadrotor control, but practical progress remains fragmented across task-specific settings. To su…

cs.RO2026

StableTracker: Learning to Stably Track Target via Differentiable Simulation

Fanxing Li, Shengyang Wang, Fangyu Sun +5

Existing FPV object tracking methods heavily rely on handcrafted modular pipelines, which incur high onboard computation and cumulative errors. While learning-based approaches have…