---
publication_id: "OT-2026-000000283"
title: "Autonomous drone swarm system with AI-driven coordination and multi-modal sensor integration"
published_at: "2026-09-15T19:02:41.992588Z"
canonical_url: "https://opentechnical.org/p/OT-2026-000000283"
categories:
  - "sensors-controls-machine-vision/industrial-control"
keywords:
  - "g05d1/6985"
  - "g05b13/027"
  - "g05d1/223"
  - "g05d1/87"
  - "g05d2105/85"
  - "g05d2109/20"
---

# Autonomous drone swarm system with AI-driven coordination and multi-modal sensor integration

## Abstract

An autonomous drone swarm system and method utilizing artificial intelligence for coordinated operations comprises command drones equipped with large language model processors and subordinate drones coordinated through a hierarchical Queen-Worker architecture. The system processes natural language commands, generates autonomous mission plans, and coordinates multi-drone operations through an encrypted self-healing mesh communication network utilizing laser, radio frequency, and visual communication channels. Multi-modal sensor integration including electro-optical, infrared, LiDAR and photogrammetry, radio frequency, and chemical detection provides comprehensive environmental awareness while federated learning algorithms enable distributed coordination in signal-denied environments. The system implements configurable operational modes spanning tactical (15 minutes-2 hours over 2 to 5 square kilometers), operational (6-24 hours over 20 to 50 square kilometers), and strategic (7-30+days over 200 to 500 square kilometers) mission profiles for military and commercial applications. Fault-tolerant protocols ensure continued operation despite individual failures through automatic task redistribution and leader election procedures.