MSE in Robotics Engineering

The MSE (RE) program is designed so that graduates will have:

a) a strong background in theories and a good knowledge of the latest technologies in the robotics engineering discipline.

b) an ability to conduct research in advanced engineering fields. The students will possess appropriate skills in formulating problems, designing experiments, collecting, processing, analyzing and interpreting data, designing a system, component, or process to meet desired requirements, and evaluating the system performances.

c) an ability to learn the latest research advancement, use advanced techniques and modern engineering tools in engineering practice, evaluate different strategies to derive a feasible solution.

Undergraduate Degree Required

Bachelor's degree in physical or mathematics sciences with an overall GPA of 3.0 or higher

Students from other related fields may be required to take preparatory courses before or after starting the program. 

Standardized Test Scores

GRE not required

Prerequisite Courses

• Ordinary Differential Equations (MATH 216 or equivalent)
• Linear Algebra (MATH 217 or equivalent
• Probability and Statistics (IMSE 317 or equivalent)
• Dynamics (ECE 347 or equivalent)
• Data Structures and Algorithms (ECE 270 and ECE 370 or equivalent)

Other Experience Required

Computer programming (no particular language or methodology)

The Robotics Engineering program is also offered online through CECS Online. The online courses utilize video streaming of the lectures given on campus. The online students have the opportunity to interact with the instructors and with fellow students (both on campus as well as online) through CANVAS. The class lectures, notes, and discussions are posted on CANVAS for online students' access. 

Course Exemptions

Please be aware that CECS does not allow for course waivers. However, students may petition for course exemptions in instances where a core course in a graduate program may not be available, may no longer be offered due to program changes, or the student may have taken a course with equivalent content. Previous undergraduate or graduate coursework deemed substantially similar to MSE core courses may qualify to exempt students from those core courses. Exempted courses must be replaced with ECE courses from within the degree program. An approved course exemption does not reduce the total number of credit hours needed to satisfy program requirements. 

Transfer of Credit

Students who have satisfied all conditions for full or conditional admission and are enrolled in good standing in their graduate program may be eligible to transfer up to a maximum of 6 credit hours of related graduate-level courses from other accredited degree-granting universities with graduate degree programs. These 6 transfer credits of previous equivalent graduate coursework can be applied to the degree only if those credits have not been counted toward a degree and have a final grade of B (3.0) or better. Students seeking transfer credit must abide by the criteria for transferring credit for master’s programs as outlined on the Request for Graduate Transfer Credit application and in accordance with the campus’s Transfer Credit Policy. It is the responsibility of the student requesting transfer of credit to submit this completed form and an official transcript with course final grade and a copy of the course syllabus or the catalog’s description.

Exemptions and transfer credit are granted at the discretion of the program chair.

Required

• ECE 5001 Analytic and Comp Math
• ECE 545 Introduction to Robotic Systems

Select ONE of the following:

• ECE 543 Kinematics, Dynamics, and Control of Robots
• ECE 544 Mobile Robotics

Choose three courses from the following:

Sensing and Processing

• ECE 555 Stochastic Processes
• ECE 580 Digital Signal Processing
• ECE 582 Statistical Signal Processing
• ECE 584 Speech Processing
• ECE 586 Digital Image Processing
• ECE 587 Selected Topics in Computer Vision
• ECE 588 Robot Vision
• ECE 642 Robotic Embed Sys
• IMSE 606 Advanced Stochastic Processes

Systems and Control

• ECE 560 Modern Control Theory
• ECE 565 Digital Control Systems
• ECE 567 Nonlinear Control Systems
• ECE 643 Humanoid Robots
• ECE 644 Advanced Robotics
• ECE 661 System Identification & Adaptive Control
• ECE 665 Optimal Control

Machine Learning and Reasoning

• ECE 528 Cloud Computing
• ECE 537 Data Mining
• ECE 552 Fuzzy Systems
• ECE 574 Adv Software Technq in Eng Appl
• ECE 5752 Reconfigurable Computing
• ECE 579 Intelligent Systems
• ECE 5831 Pattern Recognition and Neural Networks

Autonomous Vehicles

• ECE 531 Intelligent Vehicle Systems
• ECE 532 Auto Sensors and Actuators
• ECE 533 Active Automotive Safety Systems
• ECE 535 Mob Dev & Ubiqys Comp Sys
• ECE 554 Embedded Systems
• ECE 566 Mechatronics
• ECE 5701 Intro to Wireless Communications
• ECE 577 Engineering in Virtual World
• ECE 679 Advanced Intelligent Systems

Students may complete the professional elective in several ways: (1) Elect the thesis ECE 699 (6 credits) to work under the supervision of a faculty advisor, (2) Take directed study by ECE 591 (3 credits) and another RE course at graduate level, (3) take another two RE courses listed in Section II.

Students should select a minimum of 4 and a maximum of 6 credit hours of courses from other disciplines. Some courses from outside ECE may not meet cognate requirements. Please check with the ECE Department prior to registering.

Students with an inadequate background in Robotics/Electrical/Computer Engineering may be required to meet with the department graduate advisor to determine the need for preparatory courses.