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A project-based platform for students’ Robot Operation System (ROS) programming experience

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Conference

2022 ASEE Annual Conference & Exposition

Location

Minneapolis, MN

Publication Date

August 23, 2022

Start Date

June 26, 2022

End Date

June 29, 2022

Conference Session

Computers in Education 2 - Programming 2

Page Count

15

DOI

10.18260/1-2--41272

Permanent URL

https://peer.asee.org/41272

Download Count

717

Paper Authors

biography

Yizhe Chang

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Yizhe Chang is an assistant professor in mechanical engineering.

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Yifan Wang

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Zhou Zhang New York City College of Technology

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Abstract

Robot Operating System (ROS) is an open-source software framework for robot automation. ROS includes a protocol of robot commanding and integrates with a collection of software libraries. ROS aims to simplify the task of creating complex and robust robot behavior across a wide variety of robotic platforms. Currently, ROS is the major robotics software framework for researchers in graduate schools. One of the obstacles in exposing ROS to students is lacking appropriate projects for starters. ROS is not learner-friendly for its steep learning curve and comprehensive programming background needed. In this article, a robotics platform is designed by the author’s institution, based on an iRobot Create robot, is introduced. The robotics platform that includes a mobile base, a webcam, and a Lidar, can fully support ROS-based programming for autonomous navigation. To help students start ROS programming practicing, a ROS-based student autonomous navigation project, including components of path-planning, image recognition, and simultaneous localization and mapping (SLAM) is implemented on this robotics platform. A pilot study shows that the platform is favored by students and inspiring for students to learn ROS. However, the curriculum needs improvements to ensure the students’ success in completing the tasks.

Chang, Y., & Wang, Y., & Zhang, Z. (2022, August), A project-based platform for students’ Robot Operation System (ROS) programming experience Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41272

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