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Engineering case study
Seekr
An offline spatial organizer that converts LiDAR and ARKit scans into searchable 3D room maps with structured object data and portable exports.
- Role
- Independent Software Engineer
- Timeline
- Sept. 2025 - Present
- Platform
- iOS / iPadOS
- Status
- Released
Overview
An offline iPhone and iPad spatial organizer that turns LiDAR and ARKit scans into searchable 3D room maps with structured object metadata and portable exports.
Contributions
- Built semantic object search, hierarchy tags, full-text retrieval, and OBJ/PLY export around saved spatial scans.
- Created a Swift-to-Objective-C++/C++ bridge that streams ARKit odometry into RTAB-Map SLAM while returning SwiftUI-safe mapping and export callbacks.
- Designed hybrid persistence across Core Data metadata, canonical geometry assets, RTAB-Map databases, and disk-cache restoration.
- Added encrypted peer-to-peer sharing, throttled scan updates, and explicit native resource cleanup for long sessions.
System design
| Tracking | ARKit supplies device pose and LiDAR data during scanning. |
|---|---|
| Mapping | RTAB-Map maintains spatial state through a C++ layer connected by Objective-C++. |
| Persistence | Core Data stores searchable metadata while geometry and SLAM databases remain as canonical files. |
| Sharing | MultipeerConnectivity transfers scans directly between nearby devices without requiring a cloud account. |
Outcome
A portable spatial data system whose scanning, indexing, persistence, restoration, and sharing workflows are designed to work offline.
Core stack · ARKit · RTAB-Map · C++ · Objective-C++ · Core Data · MultipeerConnectivity
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