​Master of Engineering in Robotics

The principal goal of the Master of Engineering in Robotics (MEngR) degree program is to prepare individuals for professional practice in robotics engineering by leveraging the technical skills developed in an undergraduate engineering or physical science program. It is designed to be completed in 1.5 years, but it can be completed over a longer time period on a part-time basis. In order to finish in 1.5 years, students should take three courses (9 units) each in fall and spring semesters and four courses (12 units) in the second fall semester. For this program, the supervised project (6 units) is optional.

The degree requires 30 units. The courses must be 400-level or higher and they must include at least 15 units of 500-level courses. Students must have a cumulative grade point average of at least 3.2 out of a possible 4.0 over all courses applied toward the degree.

Required courses (12 units) for the MEngR degree include:

ESE 446Robotics: Dynamics and Control (Spring)3
ESE 447Robotics Laboratory (Fall, Spring)3
ESE 551Linear Dynamic Systems I (Fall)3
CSE 511AIntroduction to Artificial Intelligence3
or CSE 517AMachine Learning
ESE 590Electrical & Systems Engineering Graduate Seminar (must be taken each semester)0
Total Units12


Elective Courses (18 units): At least one elective course must be selected from each of the following three groups. Other courses may be selected as electives with the approval of the program director.

Optimization and Simulation Group

ESE 403Operations Research (Fall)3
ESE 407Analysis and Simulation of Discrete Event Systems (Spring)3
ESE 415Optimization (Spring)3

Control Engineering Group

ESE 441Control Systems (Fall)3
or
Modeling, Simulation and Control (Spring)
ESE 444Sensors and Actuators (Fall)3
ESE 425Random Processes and Kalman Filtering (Fall)3
ESE 543Control Systems Design by State Space Methods (Fall)3
ESE 552Linear Dynamic Systems II (Spring)3
ESE 553Nonlinear Dynamic Systems (Spring)3

Computer Science Group

CSE 511AIntroduction to Artificial Intelligence3
CSE 517AMachine Learning3
CSE 520SReal-Time Systems (Fall)3
CSE 521SWireless Sensor Networks3
CSE 546TComputational Geometry3
CSE 553SAdvanced Mobile Robotics (Spring)3
CSE 556AHuman-Computer Interaction Methods (Fall)3
CSE 568MImaging Sensors (Spring)3
CSE 559AComputer Vision (Spring)3


Project Course: The MEngR program may include up to 6 units of project in the form of Independent Study as part of elective courses. The independent study could be in the form of a practicum or a special project and it requires approval from the program director.

ESE 500Independent Study (Fall, Spring and Summer)var.
CSE 500Independent Study (Fall, Spring and Summer)var.
MEMS 500Independent Study (Fall, Spring and Summer)var.


Preparation for the MEngR Program

The required courses assume the following foundations in mechanical engineering and materials science, electrical engineering, systems engineering, and computer science. Although they do not count toward the degree program, they are recommended for those students who lack these foundations.

  • MEMS 255 Engineering Mechanics II (mechanical engineering and materials science foundation, fall and spring)
  • ESE 351 Signals and Systems (electrical and systems engineering foundation, fall and spring)
  • CSE 501N Programming Concepts and Practice (computer science foundation, fall)
  • A maximum of 6 credits may be transferred from another institution and applied toward the Master of Science degree. Regardless of subject or level, all transfer courses are treated as electives and do not count toward the requirement of 15 credit hours of graduate-level electrical engineering courses.
  • ESE 590 Electrical & Systems Engineering Graduate Seminar must be taken each semester. Master of Science students must attend at least three seminars per semester.
  • The degree program must be consistent with the residency and other applicable requirements of Washington University and the School of Engineering & Applied Science.
  • Students must have a cumulative grade point average of at least 3.2 out of a possible 4.0 over all courses applied toward the degree.