Robotics and Autonomy

Major: Robotics and Autonomy
Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Total Credit Hours: 45.0
Co-op Option: None
Classification of Instructional Programs (CIP) code: 14.4201
Standard Occupational Classification (SOC) code:
11-9041

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.

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.

For additional information on how to apply, visit Drexel's Admissions page for Robotics and Autonomy.

Degree Requirements

Foundation Courses6.0
Choose 2 courses in mathematics and/or signal processing
Mathematics
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
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
Perception3.0
Pattern Recognition
Fundamentals of Computer Vision
Fundamentals of Image Processing
Wireless Systems
Special Topics in ECET
Cognition and Behavior3.0
Introduction to Artificial Intelligence
Introduction to Computer Vision
Machine Learning
Cognitive Systems
Action3.0
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
Control3.0
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
Transformational Electives6.0
Choose 2 elective courses that promote the development of leadership, communication, and ethics *
Technical Writing
Theories of Communication and Persuasion
Culture, Society & Education in Comparative Perspective
Globalization and Educational Change
Mastery6.0
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 six credits of additional coursework in a Technical Focus Area. Graduate Co-op is encouraged for non-thesis students, but is not required.
Experiential Learning (optional)
Total Credits45.0

Sample Plan of Study

First Year
FallCredits
ECES 511Fundamentals of Systems I3.0
ECES 681Fundamentals of Computer Vision3.0
MEM 591Applied Engr Analy Methods I3.0
 Term Credits9.0
Winter
ECES 512Fundamentals of Systems II3.0
ECES 642Optimal Control3.0
ECES 631Fundamentals of Deterministic Digital Signal Processing3.0
 Term Credits9.0
Spring
CS 613Machine Learning3.0
ECES 513Fundamentals of Systems III3.0
EDGI 512Globalization and Educational Change3.0
 Term Credits9.0
Second Year
Fall
CS 510Introduction to Artificial Intelligence3.0
ECE 697Research3.0
MEM 571Introduction to Robot Technology3.0
 Term Credits9.0
Winter
CS 583Introduction to Computer Vision3.0
ECE 697Research3.0
EDGI 510Culture, Society & Education in Comparative Perspective3.0
 Term Credits9.0
Total Credit: 45.0
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