# FlightAR: AR Flight Assistance Interface with Multiple Video Streams and Object Detection Aimed at Immersive Drone Control

arXiv: https://arxiv.org/abs/2410.16943 · HTML: https://mlsanity.com/paper/2410.16943/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Oct 2024.

## Built on by (most cited first, 2 of 2)

- [UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation](https://mlsanity.com/paper/2501.05014/) (2025)
- [UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning](https://mlsanity.com/paper/2505.07236/) (2025)

## Abstract (arXiv)

The swift advancement of unmanned aerial vehicle (UAV) technologies necessitates new standards for developing human-drone interaction (HDI) interfaces. Most interfaces for HDI, especially first-person view (FPV) goggles, limit the operator's ability to obtain information from the environment. This paper presents a novel interface, FlightAR, that integrates augmented reality (AR) overlays of UAV first-person view (FPV) and bottom camera feeds with head-mounted display (HMD) to enhance the pilot's situational awareness. Using FlightAR, the system provides pilots not only with a video stream from several UAV cameras simultaneously, but also the ability to observe their surroundings in real time. User evaluation with NASA-TLX and UEQ surveys showed low physical demand (μ=1.8, SD = 0.8) and good performance (μ=3.4, SD = 0.8), proving better user assessments in comparison with baseline FPV goggles. Participants also rated the system highly for stimulation (μ=2.35, SD = 0.9), novelty (μ=2.1, SD = 0.9) and attractiveness (μ=1.97, SD = 1), indicating positive user experiences. These results demonstrate the potential of the system to improve UAV piloting experience through enhanced situational awareness and intuitive control. The code is available here: https://github.com/Sautenich/FlightAR