Heterogenous Swarm Control through Artificial Intelligence-embodied Architecture

Current methods of heterogeneous swarming control often involve individual entities with incompatible messaging protocols, ridged data interpretation, and lack of broader situational awareness, generating a protocol/perception problem that results in fragmented decision-making. Model Context Protocol (MCP), Large Language Models (LLMs), and related Agentic AI architectures, can enable a Universal Serial Bus Type C (USB-C) solution to this fragmentation problem by allowing individual entities to communicate with human operators or other entities through natural language. The Department of the Navy is seeking development of Agentic AI-enabled COTS small UAVs or small UGVs USB-C capabilities for demonstration of applicability in Naval and Marine Corps tasks. The goal is to deliver a small heterogenous swarm of low-cost uncrewed systems capable of receiving tasks through a natural language interface and performing complex tasks such as inspection of a facility for damage, evaluating road conditions, conducting security operations, and/or intercepting of other platforms. Performers should focus on software development to run on low cost and edge compute devices attached to highly expendable COTS platforms. Submissions will leverage preexisting DoW compliant hardware deployments using either compute resources organic to the UAV/UGV platform or flight-ready modules (e.g., Single Board Computer NVIDIA JETSON NDAA) with favorable Size, Weight, and Power (SWAP). Submissions should identify the unique nature of their Agentic-AI capability in accomplishing the objective.