Robotics and Autonomy MS

Major: Robotics and Autonomy
Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 14.4201
Standard Occupational Classification (SOC) code:

About the Program

The graduate program in Robotics and Autonomy will educate professionals who are prepared to lead and conduct research, development, and design in robotic systems and technologies. This MS degree is built upon four foundational concepts in robotics: perception, cognition, control, and action. Roughly, these four capabilities comprise: 1) obtaining data from the robot’s surroundings (perception); 2) reasoning about how that data yields information about the robot’s environment (cognition); 3) mapping environmental information to a decision about how to react to the environment (control); and 4) translating that reaction decision into movement and an interaction with the physical environment (action).

The program is an interdepartmental program in Drexel’s College of Engineering that educates and trains students in the theory, integration, and practical application of the core engineering and computer science disciplines that comprise robotics and autonomy. To be admitted, students must have a bachelor’s degree in a STEM field or demonstrate that they have acquired sufficient experience in a technical field to be able to satisfactorily complete engineering studies at the graduate level.

Students are also encouraged to engage in thesis research. The combined thesis and research cannot exceed 9.0 credits. The MS program is organized so that a student may complete the degree requirements in less than 2 years of full-time study or 2-3 years of part-time study.

Students within the Master of Science in Robotics and Autonomy are eligible to take part in the Graduate Co-op Program, which combines classroom coursework with a 6-month, full-time work experience. For more information, visit the Steinbright Career Development Center's website.

Additional Information

For more information visit the MS in Robotics and Autonomy program and the Electrical and Computer Engineering Department website.

Admission Requirements

Applicants must satisfy general requirements for graduate admission including a minimum 3.0 GPA (on a 4.0 scale) for the last two years of undergraduate studies, as well as for any subsequent graduate work, and hold a bachelor's degree in an engineering discipline from an accredited college or university. A degree in science (physics, mathematics, computer science, etc.) is also acceptable. Applicants with degrees in sciences may be required to take a number of undergraduate engineering courses. An undergraduate degree earned abroad must be deemed equivalent to a US bachelor's.

Full-time applicants must take the GRE exam. Students who do not hold a degree from a US institution must take the TOEFL or IELTS exam within two years of application submission.

Additional Information

For more information, visit the Department of Electrical and Computer Engineering webpage.

Degree Requirements

Foundation Courses6.0
Choose 2 courses in mathematics and/or signal processing
Probability & Random Variables
Linear Algebra & Matrix Analysis
Applied Probability and Statistics I
Ordinary Differential Equations I
Complex Variables I
Applied Engr Analy Methods I
Applied Engr Analy Methods II
Applied Engr Analy Methods III
Signal Processing
Random Process & Spectral Analysis
Detection & Estimation Theory
Optimal Estimation & Stochastic Control
Fundamentals of Deterministic Digital Signal Processing
Systems Courses6.0
Choose 2 courses in robotics and autonomy from the perspective of full systems or use
Introduction to Artificial Intelligence
Machine Learning & Artificial Intelligence
Applied Machine Learning Engineering
Fundamentals of Systems I
Fundamentals of Systems II
Fundamentals of Systems III
Medical Robotics I
Medical Robotics II
Introduction to Robot Technology
Mechanics of Robot Manipulators
Industrial Application of Robots
Core Components
Take 1 course in each of the four disciplines critical to robotics
Pattern Recognition
Fundamentals of Computer Vision
Fundamentals of Image Processing
Wireless Systems
Special Topics in ECET
Nondestructive Evaluation Methods
Cognition and Behavior3.0
Introduction to Artificial Intelligence
Introduction to Computer Vision
Machine Learning
Cognitive Systems
Machine Learning & Artificial Intelligence
Applied Machine Learning Engineering
Optimal Estimation & Stochastic Control
Fundamentals of Deterministic Digital Signal Processing
Fundamentals of Systems I
Fundamentals of Systems II
Fundamentals of Systems III
Aircraft Flight Dynamics & Control I
Advanced Dynamics I
Advanced Dynamics II
Advanced Dynamics III
Applied Machine Learning Engineering
Optimal Estimation & Stochastic Control
Optimal Control
Robust Control Systems I
Robust Control Systems II
Robust Control Systems III
Theory of Nonlinear Control I
Theory of Nonlinear Control II
Theory of Nonlinear Control III
Applied Optimal Control I
Applied Optimal Control II
Advanced Topics in Optimal Control
Technical Focus Areas9.0
Take 3 courses in a maximum of two core component areas listed above
Experiential Learning (optional)
Transformational Electives6.0
Choose 2 elective courses that promote the development of leadership, communication, and ethics *
Theories of Communication and Persuasion
Culture, Society & Education in Comparative Perspective
Education for Global Citizenship, Sustainability, and Social Justice
Thesis Option: A minimum of two terms of laboratory-based research that leads to a publicly defended MS thesis. Students will be advised by a faculty member, and when applicable, a representative of industry or government sponsor.
Non-thesis Option: In lieu of the research and thesis, students will complete 6.0 credits of additional coursework in a Technical Focus Area. Graduate Co-op is encouraged for non-thesis students but is not required.
Total Credits45.0

Sample Plan of Study

First Year
ECES 5113.0ECE 6123.0ECES 5133.0VACATION
ECES 6313.0ECES 5123.0ECES 6813.0 
MEM 5913.0ECES 6423.0EDGI 5223.0 
 9 9 9 0
Second Year
ECE 6103.0ECE 6873.0  
ECE 6973.0ECE 6973.0  
MEM 5713.0EDGI 5103.0  
 9 9  
Total Credits 45
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