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Teaching Robotics Using ROS (Abstract Only)

Published:17 February 2016Publication History

ABSTRACT

The deployment of autonomous and semi-autonomous robots is likely to increase dramatically over the next decade. Recent autonomous vehicle prototypes illustrate both the rapid progress of the underlying technology and the commercial possibilities of robotics. The next few years are likely to see increased interest in robotics among both students and employers.

The Robot Operating System (ROS) is an open-source software framework for developing robotics applications. It has become a standard platform with a wide range of supported robots and a vibrant software ecosystem.

This workshop will provide a hands-on introduction to ROS. Participants will have the opportunity to write ROS-based Python programs to control a Turtlebot educational robot. We will discuss the benefits and challenges of using ROS in an undergraduate robotics course. The workshop is intended for CS educators with an interest in teaching robotics. Laptops will be provided. No experience with ROS or Python is required.

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  1. Teaching Robotics Using ROS (Abstract Only)

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              • Published in

                cover image ACM Conferences
                SIGCSE '16: Proceedings of the 47th ACM Technical Symposium on Computing Science Education
                February 2016
                768 pages
                ISBN:9781450336857
                DOI:10.1145/2839509

                Copyright © 2016 Owner/Author

                Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 17 February 2016

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                SIGCSE '16 Paper Acceptance Rate105of297submissions,35%Overall Acceptance Rate1,595of4,542submissions,35%

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