Design and Implementation of a Gesture-Controlled Robotic Platform for Applied Education in Human–Robot Interaction

Industry 5.0 places humans at the center of production systems, requiring technologies that integrate operators as active components while adapting dynamically to their physical and cognitive needs. Within this context, facilitating the learning of complex concepts becomes essential, particularly through intuitive and accessible approaches. The objective of this work is to develop a hands-on educational platform for the introduction to human–robot interaction, aligned with Sustainable Development Goal 4 (SDG4). The platform is designed to support the experiential learning of key aspects of collaboration between human and robots while simultaneously familiarizing students with practical elements, including programming, hardware implementation with microcontrollers and sensors, and the use of the Robot Operating System (ROS). The developed system is based on the use of inertial measurement units (IMUs) to capture kinematic signals, enabling real-time interaction with a collaborative robot. The platform supports both translational and orientation control, with a maximum latency of 0.3 s, ensuring responsive and effective human–robot interaction. The hands-on approach will allow students to interact directly with the test bench, putting previously learned theoretical concepts into practice, according to the principle of learn-by-doing.