MS in Robotics and Autonomy

Program Plan: MS in Robotics and Autonomy

Foundation Courses (choose 2 courses in mathematics and/or signal processing)

Course Title Prereq

Mathematics
ECES 521 Probability & Random Variables  
MATH 504 Linear Algebra & Matrix Analysis  
MATH 510 Applied Probability and Statistics I  
MATH 623 Ordinary Differential Equations I  
MATH 630 Complex Variables I  
MEM 591 Applied Engr Analy Methods I  
MEM 592 Applied Engr Analy Methods II MEM 591
MEM 593 Applied Engr Analy Methods III MEM 592

Signal Processing
ECES 522 Random Process & Spectral Analysis ECES 521
ECES 523 Detection & Estimation Theory ECES 521
ECES 604 Optimal Estimation & Stochastic Control ECES 511 and ECES 521
ECES 631 Fundamentals of Deterministic Digital Signal Processing  

Systems Courses (choose 2 courses in robotics and autonomy)

Course Title Prereq
CS 510 Introduction to Artificial Intelligence CS 520, 570, and 571
ECE 610 Machine Learning & Artificial Intelligence ECES 521
ECES 511 Fundamentals of Systems I  
ECES 512 Fundamentals of Systems II ECES 511
ECES 513 Fundamentals of Systems III ECES 512
ECES 561 Medical Robotics I  
ECES 562 Medical Robotics II ECES 562
MEM 571 Introduction to Robot Technology  
MEM 572 Mechanics of Robot Manipulators MEM 666
MEM 573 Industrial Application of Robots  

Core Components (choose 1 course in each of the four disciplines critical to robots)

Course Title Prereq

Perception
ECE 687 Pattern Recognition  
ECES 681 Fundamentals of Computer Vision  
ECES 682 Fundamentals of Image Processing ECES 631
ECET 512 Wireless Systems  
ECET t580 Special Topics in ECET  
MEM 678 Nondestructive Evaluation Methods  

Cognition and Behavior
CS 510 Introduction to Artificial Intelligence CS 520, 570, and 571
CS 583 Introduction to Computer Vision CS 520, 570, and 571
CS 613 Machine Learning CS 520, 570, and 571
CS 630 Cognitive Systems CS 520, 570, and 571
ECE 610 Machine Learning and Artificial Intelligence ECES 521
ECE 612 Applied Machine Learning Engineering  
ECES 604 Optimal Estimation & Stochastic Control ECES 511 and ECES 521
ECES 631 Fundamentals of Deterministic Digital Signal Processing  

Action
ECES 511 Fundamentals of Systems I  
ECES 512 Fundamentals of Systems II ECES 511
ECES 513 Fundamentals of Systems III ECES 512
MEM 530 Aircraft Flight Dynamics & Control I  
MEM 666 Advanced Dynamics I  
MEM 667 Advanced Dynamics II MEM 666
MEM 668 Advanced Dynamics III MEM 667

Control
ECE 612 Applied Machine Learning Engineering  
ECES 604 Optimal Estimation & Stochastic Control ECES 512 and ECE 521
ECES 642 Optimal Control ECES 512
MEM 633 Robust Control Systems I  
MEM 634 Robust Control Systems II MEM 633
MEM 635 Robust Control Systems III MEM 634
MEM 636 Theory of Nonlinear Control I  
MEM 637 Theory of Nonlinear Control II MEM 636
MEM 638 Theory of Nonlinear Control III MEM 637
MEM 733 Applied Optimal Control I  
MEM 734 Applied Optimal Control II MEM 733
MEM 735 Advanced Topics in Optimal Control MEM 734

Technical Focus Area (choose 3 courses in a maximum of two core component areas listed above)

Transformational Electives (choose 2 elective courses that promote the development of leadership, communication, and ethics)

Course Title Prereq
COM 610 Theories of Communication and Persuasion  
EDGI 510 Culture, Society & Education in Comp. Perspective  
EDGI 522 Education for Global Citizenship, Sustainability, and Social Justice (formerly EDGI 512)  

Mastery

  • 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 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.