Imagine effortlessly instructing a robot to perform complex tasks, simply by conversing with it in everyday language. Researchers are turning this vision into reality with ROS-LLM, a groundbreaking framework that empowers anyone, regardless of technical expertise, to program robots using natural language instructions within the familiar Robot Operating System (ROS) environment. This innovative approach allows users to describe tasks in plain English, like "make me a coffee," and the system intelligently translates these commands into a sequence of robotic actions. ROS-LLM goes beyond simple instructions, incorporating feedback mechanisms to refine robot behavior. If the robot makes a mistake, users can provide corrective feedback, guiding the system to learn and adapt. This iterative process enhances the robot's performance over time, making it increasingly adept at handling complex and dynamic real-world scenarios. One of the standout features of ROS-LLM is its integration with imitation learning. Users can teach the robot new skills by physically demonstrating the desired actions. This hands-on approach expands the robot's capabilities, allowing it to learn a wider range of tasks. Researchers put ROS-LLM to the test in a realistic kitchen setting, tasking a robot with various challenges, from preparing coffee to rearranging objects. The results were impressive, showcasing the system's ability to understand complex instructions, adapt to changing environments, and learn new skills. Further testing explored the potential of remote control, where users in Europe successfully directed a robot in Asia. While still under development, ROS-LLM represents a significant leap forward in human-robot interaction. Its intuitive interface, coupled with powerful learning capabilities, opens up exciting possibilities for various applications, from household assistance to industrial automation. The future of robotics is conversational, and ROS-LLM is leading the way.