Teaching ROS1/2 and Reinforcement Learning using a Mobile Robot and its Simulation

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Ventuzelos, V (Author) Other; Leao, G (Author) Other; Armando Jorge Sousa (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Networks and Systems

Pages: 586-598

5th Iberian Robotics Conference, ROBOT 2022

23 November 2022 through 25 November 2022

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00X-J65

DOI: 10.1007/978-3-031-21065-5_48

Abstract (EN): Robotics is an ever-growing field, used in countless applications, from domestic to industrial, and taught in advanced courses of multiple higher education institutions. Robot Operating System (ROS), the most prominent robotics architecture, integrates several of these, and has recently moved to a new iteration in the form of ROS2. This project aims to design a complete educational package meant for teaching intelligent robotics in ROS1 and ROS2. A foundation for the package was constructed, using a small differential drive robot equipped with camera-based virtual sensors, a representation in the Flatland simulator, and introductory lessons to both ROS versions and Reinforcement Learning (RL) in robotics. To evaluate the package's pertinence, expected learning outcomes were set and the lessons were tested with users from varying backgrounds and levels of robotics experience. Encouraging results were obtained, especially in the ROS1 and ROS2 lessons, while the feedback from the RL lesson provided clear indications for future improvements. Therefore, this work provides solid groundwork for a more comprehensive educational package on robotics and ROS.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13