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Introducing ROS-Projects to Undergraduate Robotic Curriculum

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Engineering Technology Division (ETD) Technical Session 2

Tagged Division

Engineering Technology Division (ETD)

Page Count

16

DOI

10.18260/1-2--43852

Permanent URL

https://strategy.asee.org/43852

Download Count

103

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Paper Authors

biography

Lili Ma New York City College of Technology

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Professor Lili Ma received her Ph.D. in Electrical Engineering from Utah State University focusing on autonomous ground vehicles. After that she did three-year post-doctoral training at Virginia Tech working with unmanned aerial vehicles (UAVs). Prior to joining the Dept. of Computer Engineering Technology at CUNY New York City College of Technology, she taught at Wentworth Institute of Technology for eight years. Her research interests are in designing coordinated control schemes for a group of autonomous robots. Her teaching interests are in designing robotic projects that promote undergraduate research and integrate interdisciplinary areas (robotics, artificial intelligence, IoT, electronics, and image processing).

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Yu Wang New York City College of Technology

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Dr. Yu Wang received her Ph.D. degree in Electrical Engineering from the Graduate Center of the City University of New York in 2009. She is an associate professor in the Department of Computer Engineering Technology at New York City College of Technology. Her research areas of interest are engineering education, biomedical sensors, modeling real-time systems, embedded system design, and machine learning.

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Chen Xu New York City College of Technology Orcid 16x16 orcid.org/0000-0001-7590-4109

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Dr. Chen Xu is an Associate Professor at the Computer Engineering Technology department at New York City College of Technology. She received her Ph.D. degree in Biomedical Engineering from the University of Connecticut. Her research areas of interest are biomedical sensors and instrumentation, image processing, signal processing, and non-invasive medical test.

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Xiaohai Li New York City College of Technology

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Xiaohai Li received his M.S. degree in Electrical Engineering from Polytechnic Institute of New York University, New York, in 2004 and Ph.D. degree
in Electrical Engineering from the Graduate Center of the City University of New York (CUNY), New York, in 2010. He worked as a Post-doc in the PRISM
Research Center in the Department of Electrical Engineering at the City College of New York of CUNY in 2010. He is currently an Associate Professor in the
Department of Compute Engineering Technology at NYC College of Technology of CUNY. He founded the City Tech Robotics Research Lab and is a co-founder of the City Tech Experiential Arts & Technology Lab (EAT Lab) at NYC College of Technology of CUNY. His current research interests include applied control systems, robotics, swarms, wireless sensor networks, computer vision and perceptual computing, and IoT/IoRT.

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Abstract

This paper describes three MATLAB-ROS-based simulation projects developed for an undergraduate robotics course. The Robot Operating System (ROS) is an open-source framework that helps researchers and developers build and reuse code between robotics applications. Adoption of ROS in the undergraduate curricula is still rare due to its demanding requirements of C++/Python/Java programming skills and familiarity with Linux. Recently, MathWorks released its ROS Toolbox, making it easier to interact with simulators like the Gazebo and ROS-supported physical robots. The MATLAB-ROS-Gazebo simulation platform allows students to utilize other MATLAB Toolboxes, such as Image Processing, Computer Vision, Visualization, and Navigation Toolboxes, for fast algorithm development and testing.

The paper presents three projects for autonomous mobile robots on the MATLAB-ROS-Gazebo simulation platform. The first project is on sensing and perception of laser scan data and its post-processing of model-based fitting. The second project is on the path planning of an autonomous mobile robot implementing the Wavefront algorithm. The third project obtains closed-loop control of the robot's behavior based on visual hints. These three projects cover the fundamental components of controlling an autonomous mobile robot, including sensing, perception, decision-making, and low-level motion control. We believe these projects will help other educators develop ROS-based simulation projects as part of a course or a stand-alone course for teaching robotics.

Ma, L., & Wang, Y., & Xu, C., & Li, X. (2023, June), Introducing ROS-Projects to Undergraduate Robotic Curriculum Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43852

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