UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation
The UAV-VLA (Visual-Language-Action) system is a tool designed to facilitate communication with aerial robots. By integrating satellite imagery processing with the Visual Language Model (VLM) and the powerful capabilities of GPT, UAV-VLA enables users to generate general flight paths-and-action plans through simple text requests. This system leverages the rich contextual information provided by satellite images, allowing for enhanced decision-making and mission planning. The combination of visual analysis by VLM and natural language processing by GPT can provide the user with the path-and-action set, making aerial operations more efficient and accessible. The newly developed method showed the difference in the length of the created trajectory in 22% and the mean error in finding the objects of interest on a map in 34.22 m by Euclidean distance in the K-Nearest Neighbors (KNN) approach. Additionally, the UAV-VLA system generates all flight plans in just 5 minutes and 24 seconds, making it 6.5 times faster than an experienced human operator. The code is available here: https://github.com/sautenich/uav-vla
Authors
- Mikhail Martynov (ORCID: https://orcid.org/0000-0001-9529-9786)
- Oleg Sautenkov (ORCID: https://orcid.org/0009-0009-0783-9830)
- Grik Tadevosyan
- Miguel Altamirano Cabrera (ORCID: https://orcid.org/0000-0002-5974-9257)
- Sausar Karaf
- Dzmitry Tsetserukou (ORCID: https://orcid.org/0000-0001-8055-5345)
- Artem Lykov (ORCID: https://orcid.org/0000-0001-6119-2366)
- Yasheerah Yaqoot
- Muhammad Ahsan Mustafa
- Aibek Akhmetkazy
Institutions
- Skolkovo Institute of Science and Technology (RU)
Publication Details
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/hri61500.2025.10974117
- Citations
- 20
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 99.87