Students interested in this major must satisfy the standard admissions criteria used by the School of Engineering, which include an undergraduate degree in a field of engineering or related area, appropriate GRE scores, and demonstrated proficiency in English. Students must also have an academic background or be able to demonstrate proficiency in computer programming, electrical circuit design, and mechanical design; students deficient in one or more of these areas may be required to take additional courses in these areas at either the graduate or undergraduate level prior to entering or early in their degree program. Students are expected to maintain a minimum grade point average of 3.0 while enrolled in the program. They must also develop a Robotics and Automation Program of Studies with an academic advisor and file this document with the Graduate Services Office by the end of their first quarter at SCU.
The degree requires completion of a minimum of 46 graduate units, to include:
This requirement is described in Engineering Graduate Programs Bulletin Chapter 4. For this degree, students are expected to complete a course in the areas of “Engineering and Society” and “Engineering and Business/Entrepreneurship.” Additional units for School’s graduate core (which is 8 units overall) are satisfied through completion of technical electives that constitute the rest of this degree program.
Students must complete at least one Applied Math 4-unit sequence in either linear algebra or probability. The additional 4 units may be completed by taking another Applied Math course or by completing 4 units of technical elective courses that have significant mathematical components (a list of applicable elective courses is maintained in the program office).
- AMTH 245 Linear Algebra I (2) and AMTH 246 Linear Algebra II (2) [or AMTH 247 Linear Algebra I & II (4)]
- AMTH 210 Probability I (2) and AMTH 211 Probability II (2) [or AMTH 212 Probability I & II (4)]
Students must complete 13 or more units of core courses covering basic mechatronic device design, mechatronic control systems, robotic kinematics/dynamics/control, and advanced sensing/perception techniques:
- ELEN 460 / MECH 207 Advanced Mechatronics I (3)
- ELEN 461 / MECH 208 Advanced Mechatronics II (3)
- ELEN 337 / MECH 337 Robotics I (2)
- ELEN 338 / MECH 338 Robotics II (2)
- 3 or 4 units of course content in advanced sensing/perception, which may be satisfied by either:
- COEN 240 Machine Learning (4), or
- COEN 340 / ELEN 640 Digital Image Processing I (2) and COEN 341 / ELEN 643 Digital Image Processing II (2)
- Other possible courses as approved by the program advisor
Students must complete a minimum of 8 units of technical electives based on the following list or by a course approved by the student’s advisor via the Program of Studies prior to enrolling in the course. Students are encouraged to select technical electives to build expertise in one or more application areas; a list of these application areas and their associated electives is maintained in the program office.
- AMTH 377 / COEN 279 Design and Analysis of Algorithms (4)
- BIOE 252 Computational Neuroscience (2)
- BIOE 277 Biosensors (2)
- BIOE 281 Introduction to Pattern Recognition (2)
- COEN 201 / Elen 233 Digital Signal Processing I (2) & COEN 202 / Elen 234 Digital Signal Processing II (2) [or COEN 201e / Elen 233e Digital Signal Processing I & II (4)]
- COEN 240 Machine Learning (4)
- COEN 242 Big Data (4)
- COEN 243 Internet of Things (4)
- COEN 266 Artificial Intelligence (4)
- COEN 277 User Experience Research & Design (2)
- COEN 281 Pattern Recognition and Data Mining (4)
- COEN 317 Distributed Systems (4)
- COEN 319 Parallel Programming (4)
- COEN 340 / ELEN 640 Digital Image Processing I (2) & COEN 341 / ELEN 643 Digital Image Processing II (2)
- COEN 342 Deep Learning
- COEN 344 / ELEN 644 Computer Vision I (2) & COEN 345 / ELEN 645 Computer Vision II (2)
- COEN 376 Expert Systems (4)
- ELEN 235 Estimation (2)
- ELEN 236 Linear Control Systems (2)
- ELEN 237 Optimal Control (2)
- ELEN 238 / MECH 420 Model Predictive Control (2)
- ELEN 239 Introduction to Self-Driving Car Technology (4)
- ELEN 271 Microsensors (2)
- ELEN 329 / MECH 329 Introduction to Intelligent Control (2)
- ELEN 331(L) Autonomous Driving Systems (and Lab)
- ELEN 333 Digital Control Systems (2)
- ELEN 335 Estimation II (2)
- ELEN 501 Embedded Systems (2)
- ELEN 501L Embedded Systems Lab (1)
- ELEN 502 Real-Time Systems (2)
- ELEN 503 Hardware-Software Codesign (2)
- ELEN 520 Introduction to Machine Learning (2)
- ELEN 520l Introduction to Machine Learning Laboratory (1)
- MECH 218 Guidance & Control I (2) & Mech 219 Guidance & Control II (2)
- MECH 285 Computer Aided Design of Mechanisms (2)
- MECH 296A Mobile Multirobot Systems (2)
- MECH 311 Modeling and Control of Telerobotic Systems (4)
- MECH 323 Modern Control Systems I (2) and MECH 324 Modern Control Systems II (2)
- MECH 335 Adaptive Control I (2) and MECH 336 Adaptive Control II (2)
- MECH 379 Satellite Operations Laboratory (1)
Students are encouraged to complete collections of these electives to meet technology themes within the field of robotics and automation. These collections may evolve over time given technology trends.
Students must complete 6-9 units of either a Capstone Design Project or a 9-12 unit Thesis research project through an existing Capstone or Masters Thesis course in a relevant engineering department.
Additional units as required to reach a minimum of 46 units must be completed; these must be approved by the student’s advisor via the Program of Studies prior to enrolling in the courses. Typically, any extra units would be completed by enrolling in additional technical elective courses; however, in some cases, it may be of interest to take courses such as the project management or systems engineering course sequences offered by the Engineering Management program. Students may not apply the completion of one course to two different requirement categories, with the exception of the mathematics requirement.
Students may participate in this competency certification system to develop verified capabilities, acknowledged through the awarding of a “badge,” in a variety of areas that are in great demand by employers. Some of these badges will be obtained through completion of courses within the program. Others may be incorporated into the required “culminating experience.” There may also be opportunities to participate in co-curricular non-credit workshops in some topics. Management of these competency badges are managed through an online design portfolio system available to all students.