10 papers · 1 filter
Asymmetric physics enables efficient learning in quadrupedal robot swarms
Yuang Zhang, Yunlong Song, Zhihao He +7
Animal collectives navigate cluttered environments through local coordination, yet robot swarms still struggle to reproduce this capability in the physical world. End-to-end learni…
Autonomous FPV Flight with Translational Optical Flow and Uncertainty Mask
Yang Deng, Yu Hu, Feng Yu +2
Autonomous FPV quadrotor flight in complex environments using a monocular RGB camera as the sole exteroceptive sensor remains a fundamental challenge. Recent research has shown tha…
RoboWits: Unexpected Challenges for Robotic Creative Problem Solving
Chunru Lin, Hongxin Zhang, Fenghao Yu +5
The ability to reason, adapt, and creatively solve problems under unexpected challenges is essential for robots operating in real-world environments. However, current robotic bench…
Vision-Based End-to-End Learning for UAV Traversal of Irregular Gaps via Differentiable Simulation
Linzuo Zhang, Yu Hu, Feng Yu +3
-Navigation through narrow and irregular gaps is an essential skill in autonomous drones for applications such as inspection, search-and-rescue, and disaster response. However, tra…
QuadAgent: A Responsive Agent System for Vision-Language Guided Quadrotor Agile Flight
Ao Zhuang, Feng Yu, Tianbao Zhang +2
We present QuadAgent, a training-free agent system for agile quadrotor flight guided by vision-language inputs. Unlike prior end-to-end or serial agent approaches, QuadAgent decoup…
Vector Field Augmented Differentiable Policy Learning for Vision-Based Drone Racing
Yang Su, Feng Yu, Yu Hu +4
Autonomous drone racing in complex environments requires agile, high-speed flight while maintaining reliable obstacle avoidance. Differentiable-physics-based policy learning has re…
AI-IO: An Aerodynamics-Inspired Real-Time Inertial Odometry for Quadrotors
Jiahao Cui, Feng Yu, Linzuo Zhang +2
Inertial Odometry (IO) has gained attention in quadrotor applications due to its sole reliance on inertial measurement units (IMUs), attributed to its lightweight design, low cost,…
Mastering Diverse, Unknown, and Cluttered Tracks for Robust Vision-Based Drone Racing
Feng Yu, Yu Hu, Yang Su +3
Most reinforcement learning(RL)-based methods for drone racing target fixed, obstacle-free tracks, leaving the generalization to unknown, cluttered environments largely unaddressed…
Mapless Collision-Free Flight via MPC using Dual KD-Trees in Cluttered Environments
Linzuo Zhang, Yu Hu, Yang Deng +2
Collision-free flight in cluttered environments is a critical capability for autonomous quadrotors. Traditional methods often rely on detailed 3D map construction, trajectory gener…
Seeing Through Pixel Motion: Learning Obstacle Avoidance from Optical Flow with One Camera
Yu Hu, Yuang Zhang, Yunlong Song +6
Optical flow captures the motion of pixels in an image sequence over time, providing information about movement, depth, and environmental structure. Flying insects utilize this inf…