A ROS-Based Open Tool for Intelligent Robotics Education

Abstract

This paper presents an open-access platform for practical learning of intelligent robotics in engineering degrees: Robotics-Academy. It comprises a collection of exercises including recent service robot applications in real life, with different robots such as autonomous cars, drones or vacuum cleaners. It uses Robot Operating System (ROS) middleware, the de facto standard in robot programming, the 3D Gazebo simulator and the Python programming language. For each exercise, a software template has been developed, performing all the auxiliary tasks such as the graphical interface, connection to the sensors and actuators, timing of the code, etc. This also hosts the student’s code. Using this template, the student just focuses on the robot intelligence (for instance, perception and control algorithms) without wasting time on auxiliary details which have little educational value. The templates are coded as ROS nodes or as Jupyter Notebooks ready to use in the web browser. Reference solutions for illustrative purposes and automatic assessment tools for gamification have also been developed. An introductory course to intelligent robotics has been elaborated and its contents are available and ready to use at Robotics-Academy, including reactive behaviors, path planning, local/global navigation, and self-localization algorithms. Robotics-Academy provides a valuable complement to master classes in blended learning, massive online open courses (MOOCs) and online video courses, devoted to addressing theoretical content. This open educational tool connects that theory with practical robot applications and is suitable to be used in distance education. Robotics-Academy has been successfully used in several subjects on undergraduate and master’s degree engineering courses, in addition to a pre-university pilot course.

Robotics in Education: A Scientific Mapping of the Literature in Web of Science

“…It can be said that the main purpose of educational robotics is to teach students to design and create a programmable robot [21] capable of performing various actions, including moving, responding to environmental stimuli, or communicating through sound, light, or images [22][23][24]. In addition, the application of robotics in the educational field involves other associated factors in the education of students [25], including contributing to the development of logical thinking, psychomotor skills, and spatial perception of students [26], promoting student autonomy through the development of their own projects [27] and the active involvement of students in the teaching and learning process [28], promoting creativity, research, and understanding oriented toward the computer world [29], generating students' problem-solving skills [30], encouraging the development of students' digital competence [31], associating it with other pedagogical methods, such as project learning, collaborative learning, or cooperative learning [32], and encouraging functional learning given that it generates resources that can be applied in the social environment [33].…”

A Modular Multirotor Unmanned Aerial Vehicle Design Approach for Development of an Engineering Education Platform

“…The programming at that level is basically implemented through C or Python, and it depends on the control components and program tasks. Additionally, software infrastructure can be based on robot operating system (ROS) [ 8 , 9 ]. At the university level of education, the field of robotics and control theory is covered extensively in mechatronics engineering field of study through several courses.…”

Control and Simulation of a 6-DOF Biped Robot based on Twin Delayed Deep Deterministic Policy Gradient Algorithm

“…Recently, TD3 (29) and TD3's variants have been applied to some types of robots such as the manipulator arm (30,31) , 4-legged-Ant robot (32) which are simulated on the platform with the simple Pybullet environment. But it has yet to be applied and simulated for bipedal robots in ROS/Gazebo which can design complex environments and offer the possibility of practical activities with sensors (33) . Gazebo is a convenient simulation software to test these RL algorithms, and easily changing the parameters of the robot and the environment when using this software will help close the gap between the simulated environment and the real environment, which is convenient for robot control in future studies.…”