Kotlin and ROS 2 Framework Enables Natural Language Control of Robots via Android

A new tutorial published on DEV Community outlines how to build an Android component using Kotlin, Jetpack Compose, and large language models to control robotic systems through natural language instructions. The architecture connects an Android interface to a ROS 2 backend, passing through a validation layer that permits only pre-approved actions such as NAVIGATE, INSPECT, and STOP. Safety is a central design principle, requiring human confirmation for actions that could affect people or equipment, and ensuring AI-generated commands cannot bypass deterministic safety checks. The guide also recommends best practices for performance, including keeping heavy processing off the main thread and sampling high-frequency telemetry before rendering. The resulting component is designed to be extensible with NVIDIA Jetson services, computer vision models, and multimodal AI backends while keeping hardware-specific code behind interfaces for maintainability.