Robotics and autonomous systems (systems engineering), MS
The robotics and autonomous systems (systems engineering) MS degree explores interactions between complex, modern mechatronic and robotic challenges
Program description
This advanced degree emphasizes system-level competency in the rapidly growing fields of robotics and autonomous systems. The systems engineering concentration prepares students to identify, model, analyze, interpret, optimize, and manage the multidimensional interactions of increasingly complex modern mechatronic and robotic challenges.
ASU’s master’s degree in robotics and autonomous systems provides students with in-depth theoretical knowledge and practical experience in developing and controlling robotic platforms and autonomous systems. Robotics and autonomous systems are interdisciplinary technologies that are poised for increased importance in manufacturing, transportation, aerospace, defense, health care, and many other critical fields.
The systems engineering concentration is one of several options in the multidisciplinary MS program in robotics and autonomous systems, which emphasizes robotics, controls, autonomous systems, artificial intelligence, and related fields. Subjects include mechatronics, controls, foldable robotics, soft robotics, medical robotics, design, additive manufacturing, and industrial automation.
Robots take many forms but can generally be described as physical systems capable of carrying out complex tasks in their environments. Examples include autonomous cars, intelligent manufacturing robots, swarms of delivery drones, and surgical robots. In the last five years, these fields have seen tremendous growth. Both industry and academia have a pressing need for qualified personnel with deep knowledge in machine learning, artificial intelligence, adaptive control, multi-agent systems, mechanical engineering, computer science, and various other advanced topics.
Career outlook
Graduates of the Master of Science program in robotics and autonomous systems will find opportunities in both large and small corporations, government agencies, and startup enterprises, where they play critical roles.
With access to over 25 state-of-the-art labs, students gain practical experience with systems capable of carrying out complex tasks in various working environments and expand their knowledge of advanced topics such as machine learning, artificial intelligence, human-robot interaction, and adaptive control.
Possible career paths include:
- Automation Engineer
- Controls Engineer
- Machine Learning Engineer
- Robotics Engineer
- Systems Engineer
Graduates with advanced degrees have the opportunity to participate in and lead research teams developing the next generation of advanced manufacturing technologies. Our graduates are well-positioned and command top salaries in their engineering careers.
Applicants must meet the following admission requirements:
- Minimum of an earned U.S. bachelor’s degree or higher from a regionally accredited institution or the equivalent of a U.S. bachelor’s degree from an international institution that is officially recognized by that country in engineering, physical sciences, mathematics or a similar field.
- Students applying to the systems engineering concentration are expected to possess basic knowledge in key relevant areas, e.g. feedback and controls, embedded systems, programming (preferably C or similar language, MATLAB-Simulink-toolboxes) and dynamics or similar topics. See program handbook for listing of recommended academic preparation prior to admission (page 9).
- Minimum of a 3.00 cumulative GPA (scale is 4.0=A) in the last 60 hours of a student’s first bachelor’s degree program.
- Minimum of 3.00 cumulative GPA (scale is 4.0 = A) in the applicable master’s degree.
- If the applicant does not meet the minimum GPA requirements, the application may still be considered. In certain cases, demonstrated aptitude through professional experience or additional post baccalaureate education will be considered.
- An online graduate admission application, including upload of unofficial transcript(s), personal statement and resume.
- Official transcripts from each college or university attended.
- GRE is not required for this program.
- Submit a professional resume and personal statement as part of the online admissions application.
- International applicants must also meet the English proficiency requirements, as defined by Graduate Admissions. Please be sure to review the TOEFL, IELTS, or PTE score requirements, as your application will not be processed without valid proof of English proficiency.
Curriculum
The 30 credit hours must include 2 required core courses (6 credit hours), and 2 concentration courses (6 credit hours) from a focus area of interest. The remaining courses can be taken in the form of electives, in which students can choose from the approved elective list.
Curriculum overview
EGR 550 Mechatronic Systems and one of the following:
- RAS546 Robotic Systems II
- RAS557 Foldable Robotics
- RAS598 Machine Learning and AI
- RAS 598 Experimentation and Deployment of Robotic Systems
- EGR520 Engineering Analysis I
- EGR555 Mechatronics Device Innovation
- EGR560 Vehicle Dynamics and Control
- EGR598 Topic: System Control and Optimization
- EGR598 Topic: Zero Emissions Vehicles
- EGR598 Topic: Transforms and Systems Modeling
- EGR598 Topic: Mechanical Engineering Systems
- EGR598 Topic: Power Electronic Converters and Systems
- EGR608 Adv Simulation
- EGR611 Complex Engineering Systems
- IEE576 Network Optimization and Algorithms
- SER594 Software Engineering for Machine Learning
- SES598 Autonomous Exploration Systems
Courses not counted as concentration classes can be taken as electives that fall in emphasis areas. Students can take any of the concentration courses listed in the handbook as electives, or select electives from this list. Be sure to check the handbook and the linked elective list often for updates.
Elective #1
- RAS 546 Robotic Systems II
- RAS 557 Foldable Robotics
- RAS 598 Experimentation & Deployment of Robotic Systems
- MFG 598 Additive Manufacturing
- MFG 598 Micro/Nano Additive Manufacturing
- MFG 598 Multiphysics Digital Twins for Adv Mfg Processes
- EGR 555 Mechatronics Device Innovation
- AMT 570 Unmanned Aerial Systems
- SES 598 Autonomous Exploration Systems
Elective # 2
- MFG 598 Engineering Computing with Python
- MFG 598 CNC Computer Programming
- MFG 598 Programming of Industrial Robotics System
- EGR 598 System Control and Optimization
- EGR 611 Complex Engineering Systems
- EEE 587 Optimal Control
- EEE 591 Foundations of Machine Learning: from Theory to Practice
Elective # 3
- RAS 557 Foldable Robotics
- RAS 598 Machine Learning and A.I.
- MFG 598 Engineering Computing with Python
- MFG 598 Industrial Ultrasonic Testing
- MFG 598 AI in Additive Manufacturing
- MFG 598 Nondestructive Testing
- APM 598 Introduction to Deep Neural Networks
- EEE 598 Machine Learning
- MAE 551 Applied Machine Learning for Mechanical and Aerospace Engineers
Degree requirements
The MS in Robotics and Autonomous Systems with a concentration in Systems Engineering requires a minimum of 30 credit hours. These credit hours must reflect one of the following options:
- 30 credit hours and a portfolio, or
- 30 credit hours including the required Applied Project course (RAS 593), or
- 30 credit hours including the required Thesis course (RAS 599) and a thesis
Review the MS Robotics and Autonomous Systems degree requirements and coursework in the program handbook for additional information.
Application priority deadlines
August 15 Spring semester (January)
December 31 Fall semester (August)
These are priority deadlines. Applications received after this date may still be considered but are not guaranteed to be evaluated for the semester of application.
Accelerated master’s
Finish two degrees faster by combining advanced undergraduate and graduate coursework during your senior year as part of the accelerated master’s program.