A ROS-based open tool for intelligent robotics education

Abstract

This paper presents Robotics-Academy, an open-access educational platform designed for the practical teaching of intelligent robotics in engineering degrees. The tool adopts a "learn by doing" approach, allowing students to focus on developing robot intelligence—such as perception, planning, and control algorithms—by providing software templates that handle auxiliary tasks like graphical interfaces and sensor connectivity.

The platform is built on industrial standards, utilizing the Robot Operating System (ROS) middleware, the 3D Gazebo simulator, and the Python programming language. It offers a diverse collection of 18 exercises based on real-world applications, including autonomous cars, drones, and vacuum cleaners. Robotics-Academy supports both simulated and physical robots, enabling a seamless transition between virtual testing and real-world hardware. Additionally, it incorporates automatic evaluation tools for gamification and is distributed via Docker images to ensure cross-platform compatibility. The framework has been successfully implemented in various undergraduate, master’s, and pre-university courses, proving to be a robust resource for both blended and distance learning.