arXiv 2604.171902026-04-19cs.CV

LookasideVLN: 基于方向的空中视觉与语言导航

LookasideVLN: Direction-Aware Aerial Vision-and-Language Navigation

Sun Yat-sen University（中山大学）；Peng Cheng Laboratory（鹏城实验室）；The Chinese University of Hong Kong（香港中文大学）；Centre for Perceptual and Interactive Intelligence（感知与交互智能中心）；Cardiff University（卡迪夫大学）；Beihang University（北航）；Guangdong Key Laboratory of Big Data Analysis and Processing（广东大数据分析与处理重点实验室）

Yuwei Ning, Ganlong Zhao, Yipeng Qin, Si Liu, Yang Liu, Liang Lin, Guanbin Li

备注：: Accepted by CVPR 2026

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AI总结：

本文提出LookasideVLN，通过利用自然语言中的方向线索提升空中视觉与语言导航的准确性和效率，采用方向感知图、空间地标知识库和方向MLLM导航代理三种核心组件。

摘要：

空中视觉与语言导航（Aerial VLN）使无人机能够遵循自然语言指令在复杂城市环境中导航。尽管近期进展通过大规模记忆图和前瞻路径规划取得进展，但仍受限于浅层指令理解和高计算成本。现有方法主要依赖地标描述，忽视方向线索——人类导航中的关键空间上下文来源。本文提出LookasideVLN，一种利用自然语言方向线索实现更准确空间推理和更高计算效率的新范式。LookasideVLN包含三个核心组件：（1）自体视角旁侧图（ELG），动态编码与指令相关的地标及其方向关系；（2）空间地标知识库（SLKB），提供轻量级的记忆检索来自先前的导航经验；（3）旁侧MLLM导航代理，对用户指令、视觉观察和ELG中的地标方向信息进行多模态对齐以进行路径规划。大量实验表明，LookasideVLN在单层前瞻的情况下显著优于最先进的CityNavAgent，证明利用方向线索是空中VLN中强大且高效的策略。

英文摘要：

Aerial Vision-and-Language Navigation (Aerial VLN) enables unmanned aerial vehicles (UAVs) to follow natural language instructions and navigate complex urban environments. While recent advances have achieved progress through large-scale memory graphs and lookahead path planning, they remain limited by shallow instruction understanding and high computational cost. In particular, existing methods rely primarily on landmark descriptions, overlooking directional cues "a key source of spatial context in human navigation". In this work, we propose LookasideVLN, a new paradigm that exploits directional cues in natural language to achieve both more accurate spatial reasoning and greater computational efficiency. LookasideVLN comprises three core components: (1) an Egocentric Lookaside Graph (ELG) that dynamically encodes instruction-relevant landmarks and their directional relationships, (2) a Spatial Landmark Knowledge Base (SLKB) that provides lightweight memory retrieval from prior navigation experiences, and (3) a Lookaside MLLM Navigation Agent that aligns multimodal information from user instructions, visual observations, and landmark-direction information from ELG for path planning. Extensive experiments show that LookasideVLN significantly outperforms the state-of-the-art CityNavAgent, even with a single-level lookahead, demonstrating that leveraging directional cues is a powerful yet efficient strategy for Aerial VLN.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。