Testing Natural-Language Robot Control with ROS2 and MCP
We entered the instruction, “Move around the table-shaped obstacle 1.5 meters ahead and return to the starting position,” and the AI model broke it down into a sequence of movement commands and executed them in simulation.
This is not yet a demonstration of fully autonomous, sensor-based obstacle avoidance. At this stage, we are exploring the possibility of translating tasks expressed in natural language into sequences of ROS2 commands.
I’m currently working with the RobotMCP team. I’d be interested to hear where you think this approach could be most useful in real-world robot development or prototyping, as well as what limitations it might have.