# FlyMeThrough: Human-AI Collaborative 3D Indoor Mapping with Commodity Drones

**Authors:** Xia Su, Ruiqi Chen, Jingwei Ma, Chu Li, Jon E. Froehlich

arXiv: 2508.20034 · 2025-08-28

## TL;DR

FlyMeThrough is a drone-based system that uses human-AI collaboration to efficiently generate accurate 3D indoor maps with annotated points of interest, aiding navigation and space management.

## Contribution

This work introduces a novel drone-based indoor mapping system that combines commodity drones and AI for efficient 3D reconstruction and annotation of indoor spaces.

## Key findings

- Effective 3D indoor maps created in various spaces
- Stakeholder feedback supports system usefulness
- System enhances space planning and navigation

## Abstract

Indoor mapping data is crucial for routing, navigation, and building management, yet such data are widely lacking due to the manual labor and expense of data collection, especially for larger indoor spaces. Leveraging recent advancements in commodity drones and photogrammetry, we introduce FlyMeThrough -- a drone-based indoor scanning system that efficiently produces 3D reconstructions of indoor spaces with human-AI collaborative annotations for key indoor points-of-interest (POI) such as entrances, restrooms, stairs, and elevators. We evaluated FlyMeThrough in 12 indoor spaces with varying sizes and functionality. To investigate use cases and solicit feedback from target stakeholders, we also conducted a qualitative user study with five building managers and five occupants. Our findings indicate that FlyMeThrough can efficiently and precisely create indoor 3D maps for strategic space planning, resource management, and navigation.

## Full text

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## Figures

32 figures with captions in the complete paper: https://tomesphere.com/paper/2508.20034/full.md

## References

77 references — full list in the complete paper: https://tomesphere.com/paper/2508.20034/full.md

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Source: https://tomesphere.com/paper/2508.20034