Natural Language-Based Unmanned Vehicle Command Control System Using SLM

This study proposes command control system that enables military operators to intuitively control multiple Unmanned Vehicles(UVs) using natural language commands. The system employs a Sequence-to-Sequence (Seq2Seq)-based Small Language Model(SLM) that is pre-trained to interpret natural language and convert it into executable UV commands. Operators issue commands via a microphone, and the system analyzes the input to assign appropriate tasks to each UV while reporting execution results in real time. This approach reduces the training burden on military personnel, enables efficient control of multiple UVs, and enhances transparency in the command-response structure. The proposed system provides a practical technical foundation for improving the operational efficiency and reliability of UV operations in real combat environments.