Master of Science in Robotics & Autonomous Systems
The Master of Science in Robotics & Autonomous Systems has been designed to combine instruction in the underlying theoretical basis for modern robotics and autonomous systems with machine learning and hands-on experience in industry or research. Through coursework highlighting cutting-edge technologies and paid internship placements with industry partners and pioneering researchers, students graduate prepared for successful careers in industry or for further study in a doctoral program.
The College of Engineering encourages our students to tailor their academic experience by offering highly customizable master's programs, including interdisciplinary specializations and real-world opportunities. Depending on a student's individual academic interests, the duration of a master's program can vary. This program also offers part-time study options.
Degree Type
- Masters
Minimum Requirements
- 2 Semesters
- 32 Credits
Formats
- In-Person
Robotics & Autonomous Systems have become a part of everyday life, and exponential growth is anticipated in areas including medicine, transportation, supply chains, and space exploration. The Master of Science in Robotics & Autonomous Systems is designed to combine instruction in the underlying theoretical basis for modern robotics and autonomous systems with machine learning and hands-on experience in industry or research. This program is designed for students coming from any engineering or computer science bachelor’s degree program, and teaches them to synthesize engineering with machine learning.
Program Topics
- Machine Learning
- Soft Robotics
- Feedback and Control Systems
- Mechatronics
- Self-Driving Vehicles
- Smart City Technologies
- Assistive Technologies
- Environmental and Sustainable Systems
- Medical and Surgical Device Development
Amazon Robotics Day One Fellowships
Black, Latinx and Native American master’s degree students are eligible for Amazon Robotics Day One Fellowships, which cover tuition, include a stipend for living expenses and provide mentoring, networking and internship opportunities.
Internship
A unique component of the MS in Robotics & Autonomous Systems is an internship, preferably performed at one of the 120-plus robotics and autonomous systems companies in the Boston area. Students may complete an internship placement arranged through the program, arrange one independently (requires prior approval), or complete a research internship in a faculty lab. Students enrolled in the program while employed can request to use their work experience to satisfy the internship requirement.
A few industry internship partners: Amazon Robotics, Ava Robotics, Boston Scientific, DEKA, GreenSight Agronomics, MassRobotics, MathWorks, Maxar Space Robotics, Medtronic, Mitsubishi Electric Research Labs, Optimus Ride, Philips Robotics, Prodrive, PTC Realtime Robotics, Vecna Robotics, Yrobot Inc.
Coursework
Required Course (4 credits): Introduction to Robotics
The program can be completed in 2–3 semesters.
Robotics Core Course (Choose 4 courses, 16 credits) – Choose one each in Control (C), Design (D), Perception (P), and Machine Learning (ML):
Robot Motion Planning (C,P)
Medical Robotics (D)
Vision, Robotics, and Planning (C,P)
Soft Robotics (D)
Formal Methods in Robotics (C)
Cyberphysical Systems (P)
Learning from Data (ML)
Machine Learning (ML)
Technical Electives (Choose 3 courses, 12 credits)
Any graduate engineering or physical science course (500 and above) may be used as an elective (including those from the Robotics Core list above).
“Not many people can say they built a medical robotic device in the classroom. . . . I came to graduate school to change the path I was on and do something with more of a humanitarian focus, and this is exactly the class to do that.”
Franco Juliá Wise, a student in Prof. Sheila Russo’s Medical Robotics course
Career Development Resources
Looking for Robotics & Autonomous Systems interns?
Contact Prof. Roberto Tron, Director of the Master’s Program in Robotics & Autonomous Systems, to become a partner organization.