Project Based Learning Using the Robotic Operating System (ROS) for Undergraduate Research Applications
Project-based learning (PBL) has been shown to be one of the more effective methods teachers use in engineering and computer science education. PBL increases the student’s motivation in various topic areas while improving student self-learning abilities. Typically, PBL has been employed most effectively with junior- and senior-level bachelor of science (B.S.) engineering and computer science students. Some of the more effective PBL techniques employed by colleges and universities include robotics, unmanned air vehicles (drones), and computer science-based technologies for modeling and simulation (M&S). More recently, an open-source software framework for robotic and drone development, called the Robot Operating System (ROS), has been made available through the Open Source Robotics Foundation. While not an actual Operating System (OS), ROS provides the software framework for robot software and associated hardware implementation. In this paper, we examine the use of ROS as a catalyst for PBL and student activities in undergraduate research. ROS provides students, after some time investment, with the ability to develop robotic capabilities at a high level. Moreover, ROS allows a building-block approach to robotics research. The results and “how-to” data from our projects are provided on GitHub to accelerate future efforts with other PBL learning endeavors. A results-based evaluation criteria will be used as a partial measure of merit. To this end, we post usage data from cited repositories as evidence of the contribution. We will also contrast expenditure of time and effort vs. a traditional classwork environment while coupling some measure of comprehension and mastery of the underlying research topics used by the students in their undergraduate research topic.
Project-based learning (PBL)
Wilkerson, S. A., & Forsyth, J., & Korpela, C. M. (2017, June), Project Based Learning Using the Robotic Operating System (ROS) for Undergraduate Research Applications Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28768