FlightAR: AR Flight Assistance Interface with Multiple Video Streams and Object Detection Aimed at Immersive Drone Control
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 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mu=1.8,SD=0.8)$</tex> and good performance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mu=3.4,\ SD=0.8)$</tex>, proving better user assessments in comparison with baseline FPV goggles. Participants also rated the system highly for stimulation <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mu=2.35,\ SD=0.9)$</tex>, novelty <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mu=2.1,\ SD=0.9)$</tex> and attractiveness <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mu=1.97,\ SD=\ 1)$</tex>, 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/SautenichlFlightAR
Authors
- Oleg Sautenkov (ORCID: https://orcid.org/0009-0009-0783-9830)
- Daria Trinitatova (ORCID: https://orcid.org/0000-0002-0685-1418)
- Aleksey Fedoseev (ORCID: https://orcid.org/0000-0003-2506-9111)
- Dzmitry Tsetserukou (ORCID: https://orcid.org/0000-0001-8055-5345)
- Selamawit Asfaw
- Yasheerah Yaqoot
- Muhammad Ahsan Mustafa
Institutions
- Skolkovo Institute of Science and Technology (RU)
Publication Details
- Published
- 2024-12-10
- DOI
- https://doi.org/10.1109/robio64047.2024.10907428
- Citations
- 2
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 2.60
Funders
- Russell Sage Foundation