Swarical: An Integrated Hierarchical Approach to Localizing Flying Light Specks

Swarical, a Swar m-based hierarchical localization technique, enables miniature drones, Flying Light Specks (FLSs), to accurately and efficiently localize and illuminate complex 2D and 3D shapes. Its accuracy depends on the physical hardware (sensors) of FLSs used to track neighboring FLSs to localize themselves. It uses the specification of the sensors to convert mesh files into point clouds that enable a swarm of FLSs to localize at the highest accuracy afforded by their sensors. Swarical considers a heterogeneous mix of FLSs with different orientations for their tracking sensors, ensuring a line of sight between a localizing FLS and its anchor FLS. We present an implementation using Raspberry cameras and ArUco markers. A comparison of Swarical with a state of the art decentralized localization technique shows that it is as accurate and more than 2x faster.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1145/3664647.3681080
Citations
5
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
3.16
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article

Swarical: An Integrated Hierarchical Approach to Localizing Flying Light Specks

Shahram Ghandeharizadeh, Hamed Alimohammadzadeh
5 citations
Computer Graphics and Visualization Techniques
3.16
article

Swarical: An Integrated Hierarchical Approach to Localizing Flying Light Specks

Shahram Ghandeharizadeh, Hamed Alimohammadzadeh
article en
5 citations

Abstract

Swarical, a Swar m-based hierarchical localization technique, enables miniature drones, Flying Light Specks (FLSs), to accurately and efficiently localize and illuminate complex 2D and 3D shapes. Its accuracy depends on the physical hardware (sensors) of FLSs used to track neighboring FLSs to localize themselves. It uses the specification of the sensors to convert mesh files into point clouds that enable a swarm of FLSs to localize at the highest accuracy afforded by their sensors. Swarical considers a heterogeneous mix of FLSs with different orientations for their tracking sensors, ensuring a line of sight between a localizing FLS and its anchor FLS. We present an implementation using Raspberry cameras and ArUco markers. A comparison of Swarical with a state of the art decentralized localization technique shows that it is as accurate and more than 2x faster.

University of Southern California (US)
Openalex Percentile: Top 5%
Computer Graphics and Visualization Techniques
3.16
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