A Decentralized, Low-Cost Indoor Autonomous Aerial Swarm With Open-Source Intelligence

This research presents the design, implementation, and evaluation of a cost-effective indoor drone swarm system that enables autonomous, cooperative behavior among aerial robots through decentralized communication and open-source software. Inspired by natural swarming behaviors, the system allows drones to communicate directly with each other and a central Ground Control Station (GCS) using Wi-Fi, facilitating real-time data exchange and dynamic task allocation. Each drone is equipped with inertial and optical flow sensors for GPS-independent navigation, as well as LiDAR for altitude measurement. The modular architecture features a robust hardware platform constructed with lightweight materials and impact-resistant components. The software framework integrates ArduPilot, ROS, and a custom web-based interface for realtime control and monitoring. This work demonstrates how indoor drone swarms can achieve continuous operation through autonomous coordination, setting the stage for scalable indoor aerial robotics applications.

Authors

Institutions

Publication Details

Published
2025-04-11
DOI
https://doi.org/10.1109/dcas65331.2025.11045462
Citations
2
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
9.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Decentralized, Low-Cost Indoor Autonomous Aerial Swarm With Open-Source Intelligence

Prabha Sundaravadivel, Mukul V. Shirvaikar, Rafael Reyes-Ramirez, Theoren Stroud et al.
2 citations
Robotics and Sensor-Based Localization
9.99
article

A Decentralized, Low-Cost Indoor Autonomous Aerial Swarm With Open-Source Intelligence

Prabha Sundaravadivel, Mukul V. Shirvaikar, Rafael Reyes-Ramirez, Theoren Stroud, Caleb Henderson, Thomas Lyon, Ken Gibbs
article en
2 citations

Abstract

This research presents the design, implementation, and evaluation of a cost-effective indoor drone swarm system that enables autonomous, cooperative behavior among aerial robots through decentralized communication and open-source software. Inspired by natural swarming behaviors, the system allows drones to communicate directly with each other and a central Ground Control Station (GCS) using Wi-Fi, facilitating real-time data exchange and dynamic task allocation. Each drone is equipped with inertial and optical flow sensors for GPS-independent navigation, as well as LiDAR for altitude measurement. The modular architecture features a robust hardware platform constructed with lightweight materials and impact-resistant components. The software framework integrates ArduPilot, ROS, and a custom web-based interface for realtime control and monitoring. This work demonstrates how indoor drone swarms can achieve continuous operation through autonomous coordination, setting the stage for scalable indoor aerial robotics applications.

The University of Texas at Tyler (US)
Openalex Percentile: Top 3%
Robotics and Sensor-Based Localization
9.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.