The Utility of Model Context Protocols in Reconnaissance. Drones Enhancing Semantic Intelligence and Autonomy
Year: 2025
Type: article
Abstract: Reconnaissance Drones (RDs) are crucial assets in surveillance and inspection, traditionally relying on low-level Computer Vision (CV) and navigation algorithms which lack high-level reasoning. This paper explores the Model Context Protocol (MCP) as a transformative standard for integrating Large Language Models (LLMs) or Large Multimodal Models (LMMs) with drone systems. The MCP functions as a standardized cognitive interface, shifting RDs beyond simple object recognition to semantic reasoning and contextual interpretation of sensory data. This integration provides a crucial layer of cognitive intelligence, enabling superior mission planning, robust decision-making in uncertain environments, and complex task execution, thereby significantly reducing the cognitive load on human operators. The paper also discusses the feasibility of this technology for resource-constrained platforms, such as Do-It-Yourself (DIY) reconnaissance drones, advocating for a necessary hybrid architectural strategy to split processing between the on-board unit and a powerful ground station. MCP integration is deemed an achievable and necessary frontier for advancing drone autonomy and mission success.
Author: Oribe, Jon Ander
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7093324356
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