AeroDuo: Aerial Duo for UAV-based Vision and Language Navigation

TL;DR

AeroDuo introduces a dual-UAV system with high and low-altitude drones collaborating for vision and language navigation, supported by a new dataset and a framework that leverages multi-level reasoning and efficient communication.

Contribution

The paper proposes a novel dual-UAV collaborative navigation task, a new dataset HaL-13k, and an integrated framework combining large language models and lightweight policies for improved UAV navigation.

Findings

Successful demonstration of dual-UAV collaboration in complex environments.

The HaL-13k dataset enables systematic evaluation of UAV-VLN models.

AeroDuo achieves better navigation accuracy with minimal communication.

Abstract

Aerial Vision-and-Language Navigation (VLN) is an emerging task that enables Unmanned Aerial Vehicles (UAVs) to navigate outdoor environments using natural language instructions and visual cues. However, due to the extended trajectories and complex maneuverability of UAVs, achieving reliable UAV-VLN performance is challenging and often requires human intervention or overly detailed instructions. To harness the advantages of UAVs' high mobility, which could provide multi-grained perspectives, while maintaining a manageable motion space for learning, we introduce a novel task called Dual-Altitude UAV Collaborative VLN (DuAl-VLN). In this task, two UAVs operate at distinct altitudes: a high-altitude UAV responsible for broad environmental reasoning, and a low-altitude UAV tasked with precise navigation. To support the training and evaluation of the DuAl-VLN, we construct the HaL-13k, a dataset comprising 13,838 collaborative high-low UAV demonstration trajectories, each paired with target-oriented language instructions. This dataset includes both unseen maps and an unseen object validation set to systematically evaluate the model's generalization capabilities across novel environments and unfamiliar targets. To consolidate their complementary strengths, we propose a dual-UAV collaborative VLN framework, AeroDuo, where the high-altitude UAV integrates a multimodal large language model (Pilot-LLM) for target reasoning, while the low-altitude UAV employs a lightweight multi-stage policy for navigation and target grounding. The two UAVs work collaboratively and only exchange minimal coordinate information to ensure efficiency.