Course List and Program Requirements
University Core Curriculum

The world we interact in everyday and the technology that we access are built upon the foundation of embedded systems. Add to that the automation of small consumer robotic solutions and you have the core of the Robotics and Embedded Systems degree. The Robotics and Embedded Systems major provides students the systems foundation for all aspects of designing and implementing mobile and stationary robotics platforms, particularly in the area of embedded sequential control. Students will learn how to analyze, design and implement intelligent software systems for autonomous robotics platforms. Building upon the foundation of software engineering, Robotics and Embedded Systems takes the students from pure software development into product solution development.

Experience Robotics

Over the course of three hours, our students assembled this fully functional quad crawler. It is designed to take instruction to determine its path and can take input from sensors for navigation.

Robotics and Embedded Systems Objectives (BS)

Analyze problems and design, build and test software systems in a team environment using industry-standard software engineering processes encompassing all phases of the software lifecycle to solve them.
Demonstrate the ability to choose the most appropriate programming languages, standards and technologies to meet the requirements of specific projects and communicate these decisions clearly in written and oral forms.
Use multiple languages/IDEs, etc. (including at least one high level language and one lower level language) to design and build multiple robotic and embedded systems as well as design and implement software subsystems for autonomous mobile robots, including power, motor, communication/interconnection, sensors (feedback) and control subsystems.
Using fluency in schematic reading and design, design and fabricate a printed circuit board (PCB), including schematic capture, and become familiar with such processes and software required to do so.
Demonstrate fluency with transducers of multiple varieties (implementing their use as sensor subsystems in designs), develop mastery of multiple ÃŽÂ¼Controller architectures, and apply data structures, algorithms and techniques in digital signal processing to signals
received from various types of sensors; such implementations may
include FPGAs, ASICS or other technologies.
Analyze the real-time constraints of an embedded system and specify the performance requirements needed to satisfy a particular application's needs.
Investigate and apply aspects of machine learning and adaptive behaviors such as decision trees, genetic algorithms, reinforced learning and design paradigms that imitate such learning (e.g., subsumption architectures and state machines).
Make use of the principles of physical computing as they apply to human/machine interaction, including innovation of new methods, as well as kinematics of manipulators and locomotion processes, such as the analysis of walking gaits.