Chapter 16: Robotics and Automation Program

Program Advisor: Dr. Christopher Kitts

OVERVIEW

Robotics and the automation sciences relating to intelligent machines and smart systems is a burgeoning field that is fueling the economy, driving employment in Silicon Valley and beyond, and transforming the nature of work in a wide range of applications. We offer a multi-disciplinary master’s degree in Robotics and Automation, which balances deep technical expertise with practical application-oriented experience and with insight into the societal impacts, ethical challenges and entrepreneurial opportunities relevant to this field. A technical core ensures competence in the areas of design, controls and perception. Elective-based focus areas within the degree provide opportunities for students to build knowledge and expertise in application areas such as industrial internet-of-things and manufacturing, field robotics, etc. Furthermore, partnerships with local companies and agencies provide highly applicable project experiences, ensure a relevant curriculum, and contribute to a strong student recruitment pipeline. Finally, a novel co-curricular option certifies student competencies in modern skills and tools relevant to the robotics and automation industry.

MASTER’S DEGREE PROGRAM AND REQUIREMENTS

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:

  • Enrichment Experience (minimum 8 units)
    • Graduate Core: one course each from “Engineering and Business/Entrepreneurship” and “Engineering and Society” (a minimum of 4 units)
    • The additional 4 units can be satisfied by any combination of a) one or more technical electives, b) additional classes from Graduate Core List, c) Cooperative Education courses (ENGR 288/289) and d) combination of a, b and c.

Mathematics (8 units): 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)]

Technical Core (13 units): 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:

  • ECEN (ELEN) 460 / MECH 207 Advanced Mechatronics I (3)
  • ECEN (ELEN) 461 / MECH 208 Advanced Mechatronics II (3)
  • ECEN (ELEN) 337 / MECH 337 Robotics I (2)
  • ECEN (ELEN) 338 / MECH 338 Robotics II (2)
  • 3 or 4 units of course content in advanced sensing/perception, which may be satisfied by either:
    • CSEN (COEN) 240 Machine Learning (4), or
    • CSEN (COEN) 340 / ECEN (ELEN) 640 Digital Image Processing I (2) and CSEN (COEN) 341 / ECEN (ELEN) 643 Digital Image Processing II (2)
    • Other possible courses as approved by the program advisor

Technical Electives (8 units): 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 / CSEN (COEN) 279 Design and Analysis of Algorithms (4)
  • BIOE 252 Computational Neuroscience (2)
  • BIOE 277 Biosensors (2)
  • BIOE 281 Introduction to Pattern Recognition (2)
  • CSEN (COEN) 201 / ECEN (ELEN) 233 Digital Signal Processing I (2) & CSEN (COEN) 202 / ECEN (ELEN) 234 Digital Signal Processing II (2) or CSEN (COEN) 201E /ECEN (ELEN) 233E Digital Signal Processing I & II (4)
  • CSEN (COEN) 240 Machine Learning (4)
  • CSEN (COEN) 242 Big Data (4)
  • CSEN (COEN) 243 Internet of Things (4)
  • CSEN (COEN) 266 Artificial Intelligence (4)
  • CSEN (COEN) 277 User Experience Research & Design (2)
  • CSEN (COEN) 281 Pattern Recognition and Data Mining (4)
  • CSEN (COEN) 317 Distributed Systems (4)
  • CSEN (COEN) 319 Parallel Programming (4)
  • CSEN (COEN) 340 /ECEN (ELEN) 640 Digital Image Processing I (2) & CSEN (COEN) 341 /ECEN (ELEN) 643 Digital Image Processing II (2)
  • CSEN (COEN) 342 Deep Learning
  • CSEN (COEN) 344 /ECEN (ELEN) 644 Computer Vision I (2) & CSEN (COEN) 345 / ECEN (ELEN) 645 Computer Vision II (2)
  • CSEN (COEN) 376 Expert Systems (4)
  • ECEN (ELEN) 235 Estimation (2)
  • ECEN (ELEN 236 Linear Control Systems (2)
  • ECEN (ELEN) 237 Optimal Control (2)
  • ECEN (ELEN) 238 / MECH 420 Model Predictive Control (2)
  • ECEN (ELEN) 239 Introduction to Self-Driving Car Technology (4)
  • ECEN (ELEN) 271 Microsensors (2)
  • ECEN (ELEN) 329 / MECH 329 Introduction to Intelligent Control (2)
  • ECEN (ELEN) 331(L) Autonomous Driving Systems (and Lab)
  • ECEN (ELEN) 333 Digital Control Systems (2)
  • ECEN (ELEN) 335 Estimation II (2)
  • ECEN (ELEN) 501 Embedded Systems (2)
  • ECEN (ELEN) 501L Embedded Systems Lab (1)
  • ECEN (ELEN) 502 Real-Time Systems (2)
  • ECEN (ELEN) 503 Hardware-Software Codesign (2)
  • ECEN (ELEN) 520 Introduction to Machine Learning (2)
  • ECEN (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; the program web site lists current themes with affiliated industry partners and capstone/thesis opportunities. Examples include topics such as advanced manufacturing, field robotics, bio-robotics/mechatronics, aerospace robotics, automation sciences, and so on.

Culminating Experience (6-12 units): 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 Master’s Thesis course in a relevant engineering department.

Additional Units (as necessary): 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.

Modern Tools/Skills Competency Badging (Optional): 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.

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