For program contact information, please visit this website.
The multidisciplinary Master of Science program in robotics is offered by the College of Engineering and the Khoury College of Computer Sciences. The program is designed to provide students comprehensive training in algorithms, sensors, control systems, and mechanisms used in robotics.
In this degree program, students will be admitted (as of Spring 2025) to the college associated with their concentration, and their degree is awarded by that college. The concentrations are associated with the colleges as follows:
- Computer Science—Khoury College of Computer Sciences
- Electrical and Computer Engineering—College of Engineering
- Mechanical Engineering—College of Engineering
Students will follow all policies associated with their home college.
Gordon Institute of Engineering Leadership
Master's Degree in Robotics with Graduate Certificate in Engineering Leadership
Students may complete a Master of Science in Robotics in addition to earning a Graduate Certificate in Engineering Leadership. Students must apply and be admitted to the Gordon Engineering Leadership Program in order to pursue this option. The program requires fulfillment of the 16-semester-hour curriculum required to earn the Graduate Certificate in Engineering Leadership, which includes an industry-based challenge project with multiple mentors. The integrated 40-semester-hour degree and certificate will require 24 semester hours of advisor-approved robotics technical courses.
- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Complete all courses and requirements listed below unless otherwise indicated.
Core Requirements
Course List | Code | Title | Hours |
| 4 |
| Robot Mechanics and Control | |
| Control Systems Engineering | |
| 4 |
| Mobile Robotics | |
| Assistive Robotics | |
| Robotics Sensing and Navigation | |
| 4 |
| Reinforcement Learning and Sequential Decision Making | |
| Robotic Science and Systems | |
Concentrations
Complete one of the following concentrations:
Program Credit/GPA Requirements
32 total semester hours required
Minimum 3.000 GPA required
Computer Science
Course List | Code | Title | Hours |
| |
| 4 |
| Reinforcement Learning and Sequential Decision Making | |
| Robotic Science and Systems | |
| 16 |
| CS 8674 | Master’s Project | 4 |
| 12 |
| CS 8674 | Master’s Project | 4 |
| CS 7990 | Thesis | 4 |
| 8 |
Electrical and Computer Engineering
Course List | Code | Title | Hours |
| |
| 4 |
| Mobile Robotics | |
| Assistive Robotics | |
| Robotics Sensing and Navigation | |
| 16 |
| EECE 7945 | Master’s Project | 4 |
| 12 |
| EECE 7945 | Master’s Project | 4 |
| EECE 7990 | Thesis | 4 |
| 8 |
| |
Mechanical Engineering
Course List | Code | Title | Hours |
| |
| 4 |
| Robot Mechanics and Control | |
| Control Systems Engineering | |
| 16 |
| ME 7945 | Master’s Project | 4 |
| 12 |
| ME 7945 | Master’s Project | 4 |
| ME 7990 | Thesis | 4 |
| 8 |
| |
Elective Course List
Any course in the following list will serve as an elective course, provided the student satisfies prerequisites.
Course List | Code | Title | Hours |
| Mixed Reality | |
| Foundations of Artificial Intelligence | |
| Artificial Intelligence for Human-Computer Interaction | |
| Pattern Recognition and Computer Vision | |
| Computer/Human Interaction | |
| Algorithms | |
| Natural Language Processing | |
| Machine Learning | |
| Empirical Research Methods | |
| Advanced Machine Learning | |
| Deep Learning | |
| Special Topics in Artificial Intelligence | |
| Mobile Robotics | |
| Assistive Robotics | |
| Robotics Sensing and Navigation | |
| Classical Control Systems | |
| Computer Vision | |
| Data Visualization | |
| Introduction to Machine Learning and Pattern Recognition | |
| Autonomous Field Robotics | |
| Numerical Optimization Methods | |
| Information Theory | |
| Advanced Computer Vision | |
| Advanced Machine Learning | |
| Advanced Special Topics in Electrical and Computer Engineering (Legged Robots) | |
| Human Performance | |
| Statistical Methods in Engineering | |
| Human Factors Engineering | |
| Neural Networks and Deep Learning | |
| Computer Aided Design and Manufacturing | |
| Mechatronic Systems | |
| Robot Mechanics and Control | |
| Elasticity and Plasticity | |
| Dynamics and Mechanical Vibration | |
| Control Systems Engineering | |
| Musculoskeletal Biomechanics | |
| Mathematical Methods for Mechanical Engineers 1 | |
| Introduction to Microelectromechanical Systems (MEMS) | |
| Wearable Robotics | |
| Advanced Control Engineering | |
| Motor Control | |
| Applications of Biomechanics in Human Function and Movement | |
| Experimental Design and Applied Statistics | |
| Technologies in Movement and Rehabilitation Science | |
