arXiv AI By Aditya Azad, Arthur Huang, Guanrui Li

ClearNav: Perception-Aligned Quadrotor Flight Using Differential-Physics

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arXiv Computer Vision
Oct 23

KinoUAV: A Benchmark for Safe and Stable UAV Vision-Language Navigation with Kinodynamic Modeling

KinoUAV introduces a kinodynamic benchmark for UAV vision-language navigation, featuring a dataset and an agent that generate trajectories under velocity, acceleration, and jerk constraints. The benchmark incorporates directional free-space distance labels to guide safe motion decisions and a Cruise-Seek task that eases target search. Experiments show the KinoUAV-Agent achieves higher success rates with lower yaw and collision rates than existing methods.

By Chenyao Yang, Peijin Wang, Yingchao Feng, Wenhui Diao
arXiv AI
Sep 18

VLN on the Fly: An Onboard Vision-Language Navigation Stack for Aerial Robots

The paper introduces VLN on the Fly, an onboard vision‑language navigation stack for aerial robots that separates grounding, planning, and control into inspectable stages. A quantized vision‑language model grounds instructions to a coarse image cell, depth estimation lifts this to a 3D goal, a fast B‑spline planner generates a feasible trajectory, and a pretrained reinforcement learning policy translates the trajectory into motor commands. In controlled indoor flights, the stack achieved the target in 13 of 15 trials with a mean goal error of 5.72 cm and 39.3% GPU utilization, and successfully tracked collision‑free trajectories in cluttered environments.

By Marco S. Tayar, Felipe Tommaselli, Gianluca Capezutto, Pedro Antonio Rabelo Saraiva, Pedro H. V. de Freitas, Lucas Kido, Guilherme Sonego, Ricardo V. Godoy, Marcelo Becker
Hugging Face Trending Papers
Jun 18

See-and-Reach: Precise Vision-Language Navigation for UAVs within the Field of View

UAV Vision-Language Navigation (UAV-VLN) is typically formulated as a holistic search-and-reach problem, where long-range target discovery and final target approach are optimized and evaluated jointly. This formulation makes it difficult to assess a critical capability of aerial embodied agents, namely whether a UAV can accurately ground a visible target and translate vision-language evidence into precise 3D motion once the target enters its field of view.

arXiv AI
Jun 19

See-and-Reach: Precise Vision-Language Navigation for UAVs within the Field of View

arXiv:2606. 20045v1 Announce Type: cross Abstract: UAV Vision-Language Navigation (UAV-VLN) is typically formulated as a holistic search-and-reach problem, where long-range target discovery and final target approach are optimized and evaluated jointly.

By Fanfu Xue, En Yu, Yantian Shen, Zhikun Hu, Hongjun Wang, Yang Yang, Xindi Wang, Jiande Sun
arXiv Machine Learning
Jul 28

Anticipatory Risk-Guided Reinforcement Learning for Safe Flight Through Dynamic Clutter

arXiv:2607. 23565v1 Announce Type: cross Abstract: Safe quadrotor navigation in cluttered and dynamic environments depends not only on instantaneous geometric perception, but more critically on anticipating collision risks induced by relative motion.

By Yuchao Mei, Guohao Zhang, Luxia Ai, Haopeng Chen, Wenbing Tao