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Abstract:Artificial intelligence integrated with drone command and control (physical AI) offers a route to autonomy through large language models (LLMs), yet a unified LLM-to-drone interface has been missing. We present an LLM-agnostic command-and-control interface and agentic harness joining the Model Context Protocol (MCP) to MAVLink, the near-universal drone command-and-telemetry standard: "DroneServer" gives any MCP-capable LLM command, telemetry, mission, and safety functions over ArduPilot and PX4. Its 98 tools cover 223 of 238 client-side methods of MavSDK, MAVLink's library; 61 of the 98 were exercised in software-in-the-loop. We treat the LLM as an untrusted commander: zero public ports (externally verified); every command validated server-side (tiers, confirmation handshakes, independent geofence, audit log), exercised by an adversarial safety suite. Server-side mission state resolves the "fire-and-forget" mismatch: a scripted client's 37.8-minute mission survived a 4-minute disconnection. Over 1,000 simulated flights ran a ten-mission LLM-UAV control benchmark; eight of eleven models complete 90.0-100% of its six flying missions, and no aircraft left the permitted zone in 110 geofence-violation trials. On real hardware, the unmodified server commanded three quadcopters, GPS-guided and GPS-denied; five providers' models flew an unseen mission, ten of ten. The tests and datasets include: repeated trials, standardized evaluation tasks, success/failure statistics, latency analysis, uncertainty treatment, comparative benchmarking across models/platforms, prompt sets, mission complexity, tool-call traces, safety-intervention logs, and safety-performance assessment. The architecture is a scaffold for a higher-level drone-LLM operating system where plain-language commands realize complex missions, and a path to agent swarms commanding drone swarms under one security umbrella.

Submission history

From: Peter John Burke [view email]
[v1] Wed, 21 Jan 2026 21:37:54 UTC (11,066 KB)
[v2] Wed, 6 May 2026 16:49:55 UTC (10,454 KB)
[v3] Fri, 11 Sep 2026 14:01:42 UTC (18,788 KB)