WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation 文章

ArXiv CS.AI2026-06-06NEWSen作者: Shengtao Zheng, Kai Li, Weichen Zhang, Yu Meng, Chen Gao, Xinlei Chen, Yong Li, Xiao-Ping Zhang

详细信息

来源站点
ArXiv CS.AI
作者
Shengtao Zheng, Kai Li, Weichen Zhang, Yu Meng, Chen Gao, Xinlei Chen, Yong Li, Xiao-Ping Zhang
文章类型
NEWS
语言
en
发布日期
2026-06-06

摘要

arXiv:2606.06147v1 Announce Type: new Abstract: End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict actions, often struggling in dense urban environments where severe occlusions and sharp turns result in drastic viewpoint transitions. We argue that the ability to "imagine" future states -- inherent in World Models -- is critical for robust decision-making under such partial observability. To address this, we construct a challenging Urban Canyon Traversal Benchmark, specifically designed to evaluate spatial understanding in scenarios characterized by severe occlusions and drastic viewpoint transitions.