Search for: All records

Robotics education is often constrained by the high cost and limited accessibility of physical robots, which can hinder the learning experience for many students. To address this challenge, the Fundamentals of Robotics Education (FORE) project, part of a larger NSF-funded collaborative work, was developed to create an accessible and comprehensive online learning platform. FORE provides a student-centered approach to robotics education, featuring a robust code editor, real-time simulation, and interactive lessons. This paper presents the architecture and implementation of the FORE platform, highlighting its key components, including the backend simulation using Gazebo and ROS2, a frontend visualizer built with Three.js, and the integration of a Python-based coding environment. We discuss the development process, the contributions of the student team, and the challenges encountered during the project. The results demonstrate the platform’s effectiveness in making robotics education more easily available. These findings originate from software testing and utilization by senior computer science students, as well as feedback from participants at the University of Nevada, Reno College of Engineering’s annual Capstone Course Innovation Day. The platform allows students to gain hands-on experience without the need for physical hardware. Its adaptability enables it to serve a broad audience of undergraduate students, offering an encompassing and accessible solution for modern robotics education. 

Recent advancements in robotics, including applications like self-driving cars, unmanned systems, and medical robots, have had a significant impact on the job market. On one hand, big robotics companies offer training programs based on the job requirements. However, these training programs may not be as beneficial as general robotics programs offered by universities or community colleges. On the other hand, community colleges and universities face challenges with the required resources, especially qualified instructors, to offer students advanced robotics education. Furthermore, the diverse backgrounds of undergraduate students present additional challenges. Some students bring extensive industry experience, while others are newcomers to the field. To address these challenges, we propose a student-centered personalized learning framework for robotics. This framework allows a general instructor to teach undergraduate-level robotics courses by breaking down course topics into smaller components with well-defined topic dependencies, structured as a graph. This modular approach enables students to choose their learning path, catering to their unique preferences and pace. Moreover, our framework's flexibility allows for easy customization of teaching materials to meet the specific needs of host institutions. In addition to teaching materials, a frequently-asked-questions document would be prepared for a general instructor. If students' robotics questions cannot be answered by the instructor, the answers to these questions may be included in this document. For questions not covered in this document, we can gather and address them through collaboration with the robotics community and course content creators. Our user study results demonstrate the promise of this method in delivering undergraduate-level robotics education tailored to individual learning outcomes and preferences.