Master of Science in Robotics (MSR)

Welcome to the

Master of Science in Robotics

The MSR program consists of 30 credit hours of graduate level coursework, and offers a Masters thesis track or a course-based only track. The curriculum consists of a core of six (6) required courses, and four (4) electives. The latter are selected from an approved list of graduate courses and are designed to provide the opportunity for specialization in particular academic subareas such as control, estimation, optimization, or machine learning.

Students interested in our full-time campus experience are able to complete all degree requirements below, including the optional thesis, in as little as 18 to 24 months. See admission requirements and application information below.

Robotics is an interdisciplinary field that requires crossing the boundaries of traditional engineering disciplines. In the face of the rising expenditures on robotics, there will be a continuing and increasing need for skilled interdisciplinary engineers to design, build, and program robots in the future. This interdisciplinary Master of Science in Robotics (MSR) program is answering the societal, government, and industry need for specialized education in this field.

Contact us for more information
Email: msr-info@udel.edu
Phone: 302-831-2423

Click here to apply today

 

Degree Requirements

The program builds on some of the unique strengths, resources, and expertise that can be identified across the University of Delaware campus, to offer a higher education and professional training opportunity that cannot be easily replicated.
Required Courses (18 credits)

Six (6) Required Courses:
MEEG 621 Linear Systems
CISC 621 Algorithm Design and Analysis
MEEG 671 Introduction to Robotics
MEEG 678 Introduction to Autonomous Driving
CISC 642 Introduction to Computer Vision
MAST 632 Environmental Field Robotics

Graduate-Level Engineering Electives (12 credits)

Four (4) graduate-level engineering electives are required. The following courses are pre-approved:
CISC 681 Artificial Intelligence
CISC 684 Introduction to Machine Learning
MEEG 620 Intermediate Dynamics
MEEG 677 Introduction to State Estimation
MEEG 698 Stochastic Optimal Control
MEEG 829 Applied Nonlinear Control
MEEG 877 Sensing and Estimation in Robotics
MEEG 890 Nonlinear Programming
MEEG 894 Linear Feedback Control Design
MEEG 895 Game Theory & Mechanism Design
BMEG 441/667 Biomechatronics
MEEG 467/667 Soft Robots: design, Principles and Applications

Thesis Option

If pursuing the thesis option, two of the electives are substituted for Master’s thesis credits. Graduate-level independent study can substitute for up to six (6) graduate elective credits along a non-thesis degree track. Independent study activities can take place outside the campus, in the context of semester-long internships with approved industry or government partners, but always under the supervision and oversight of a faculty member from the participating academic units, who will be ultimately responsible for assigning a grade for the course.

Through their choice of technical electives, students in the MSR program have the option to select from one of five academic concentrations, each of which involves a set of three related fundamental courses.

Suggested Academic Concentrations (Optional)

We offer five (5) main concentrations, with the following suggested courses:

  1. Control:
    MEEG 621 (Linear Systems); MEEG 698 (Stochastic Optimal Control) or MEEG 894 (Linear Feed-back Control Design); MEEG 829 (Applied Nonlinear Control)
  2. Estimation:
    MEEG 621 (Linear Systems); MEEG 677 (Introduction to State Estimation); MEEG 877 (Sensing and Estimation in Robotics)
  3. Artificial Intelligence:
    CISC 621 (Algorithm Design and Analysis); CISC 684 (Intro to Machine Learning); CISC 642 (Computer Vision)
  4. Design:
    MEEG 620 (Dynamics); MEEG 671 (Intro to Robotics); MAST 632 (Environmental Field Robotics)
  5. Optimization:
    CISC 621 (Algorithms); MEEG 895 (Game Theory and Mechanism Design); MEEG 890 (Nonlinear Programming)

“My graduate studies at UD gave me adequate knowledge to kick off my first job in building self-driving cars, and laid a good foundation for my later career.”

– Caili Li, UD alumni 2017, Software Engineer at Zoox

See official program policy statement for details. For more information about this program, contact msr-info@udel.edu

Admission Requirements

The requirements for admission to the MSR program are the following:

  • A baccalaureate degree in mechanical engineering or in a closely allied field of science or mathematics. Applicants with degrees in other disciplines may be admitted with provisional status and may be required to complete prerequisite courses that are deemed necessary for appropriate preparation for courses in the program.
  • An undergraduate grade point average in engineering, science and mathematics courses of at least 3.0 on a 4.0 scale.
  • The Graduate Record Examination (GRE) combined Quantitative and Verbal score of 308 (1200). Waivers may be considered on a case-by-case basis, with documented approval by the Department of Mechanical Engineering’s Admissions Committee.
  • International applicants: The TOEFL with a minimum of 100 on the IBT and a speaking score of 20. IELTS with a minimum score of 6.5 with no individual sub-score below 6.0 on the IELTS alternative.
  • Three letters of recommendation from former teachers or supervisors.
  • Resume
  • Statement of Purpose

All items should be uploaded into your graduate application (https://grad-admissions.udel.edu/apply/). Admission is selective and competitive based on the number of well qualified applicants and the research opportunities available with the faculty. Meeting the stated minimum academic requirements does not guarantee admission.

Application Deadlines

MSR Fall Admission

  • January 31: Priority consideration for admission
  • July 31: Final deadline to apply

MSR Spring Admission

  • October 31: Priority consideration for admission
  • December 31: Final deadline to apply

Tuition rates of all programs can be seen on the Graduate Office’s Tuition webpage.

Contact us for more information
Email: msr-info@udel.edu
Phone: 302-831-2423

Program Core Faculty

Panagiotis (Panos) Artemiadis

Panagiotis (Panos) Artemiadis

Associate Professor & Graduate Program Director

HRI; Rehabilitation
Research Lab

Sambeeta Das

Sambeeta Das

Assistant Professor

Nano/Micro Robotics, Biorobotics
Research Lab

Guoquan Huang

Guoquan Huang

Assistant Professor

Estimation, Machine vision, SLAM
Research Lab

Andreas Malikopoulos

Andreas Malikopoulos

Terri Connor Kelly and John Kelly Career Development Associate Professor

Decentralized Control
Research Lab

Ioannis Poulakakis

Ioannis Poulakakis

Associate Professor

Legged Robots; Nonlinear Control
Research Lab 

Christopher Rasmussen

Christopher Rasmussen

Associate Professor

Computer Vision

Fabrizio Sergi

Fabrizio Sergi

Assistant Professor

Rehabilitation
Research Lab

Herbert Tanner

Herbert Tanner

Professor

Multi-robot Systems; Human-robot Interaction
Research Lab

Arthur Trembanis

Arthur Trembanis

Associate Professor

Oceanography
Research Lab

Affiliated Faculty

Gonzalo Arce

Gonzalo Arce

Professor

Signal Processing

Stephan Bohacek

Stephan Bohacek

Associate Professor

Wireless Networks

Charles Boncelet

Charles Boncelet

Professor

Signal Processing

Austin Brockmeier

Austin Brockmeier

Assistant Professor

Machine Learning, Signal Processing, Neural Engineering
Research Lab

Leonard Cimini

Leonard Cimini

Professor

Networks

Keith Decker

Keith Decker

Associate Professor

Multi-Agent Systems
Research Lab

Jill Higginson

Jill Higginson

Professor

Rehabilitation
Research Lab

Chandra Kambhamettu

Chandra Kambhamettu

Professor

Vision

Mark Moline

Mark Moline

Professor

Marine Science

Xi Peng

Xi Peng

Assistant Professor

Deep Learning; Computer Vision
Research Lab

Thomas Powers

Thomas Powers

Associate Professor

Ethics
Research Lab

Valery Roy

Valery Roy

Associate Professor

Micromechatronics

Vijay Shanker

Vijay Shanker

Professor

Machine Learning

Chien-Chung Shen

Chien-Chung Shen

Professor

Networks

Abhyudai Singh

Abhyudai Singh

Associate Professor

Systems/Synthetic Biology; Stochastic Hybrid Systems
Research Lab

Erin Sparks

Erin Sparks

Assistant Professor

Field-based Robotics; Biomechanics
Research Lab

Adam Wickenheiser

Adam Wickenheiser

Associate Professor

Energy; Environment

Randall Wisser

Randall Wisser

Associate Professor

Plant Science; Quantitative Genetics
Research Lab

Ryan Zurakowski

Ryan Zurakowski

Associate Professor

Mathematical Modeling
Research Lab

Research Labs and Facilities

Students will have the ability to work in state-of-the-art research labs and facilities that are unique in the University of Delaware. Students will be exposed to implementation challenges of turning theory and algorithms into a functional system that is robust enough to be deployed and be functional under real-world conditions. In fact, one of the unique aspects of the MSR program in UD is in leveraging the campus-wide facilities, expertise, and existing faculty collaborations, to expose its students within the normal curriculum, to aspects of implementation and utilization of robotic systems in air, land, and sea.

Areas of Research Interest Include:

  • HRI
  • Rehabilitation
  • Wireless Networks
  • Signal Processing
  • Machine Learning
  • Signal Processing
  • Neural Engineering
  • Networks
  • Nano/Micro Robotics
  • Biorobotics
  • Multi-agent Systems
  • Rehabilitation
  • Estimation Machine Vision
  • SLAM
  • Vision
  • Decentralized Control
  • Marine Science
  • Deep Learning
  • Computer Vision
  • Legged Robots
  • Nonlinear Control
  • Ethics
  • Computer Vision
  • Micromechatronics
  • Rehabilitation
  • Machine Learning
  • Networks
  • Systems/Synthetic Biology
  • Stochastic Hybrid Systems
  • Field-based Robotics
  • Biomechanics
  • Multi-robot Systems
  • Human-robot Interaction
  • Oceanography
  • Energy
  • Environment
  • Plant Science
  • Quantitative Genetics
  • Mathematical Modeling
  • Brain machine interfaces
  • Swarm robotics
  • Human-Swarm Interaction
“I felt confident coming out of UD that I could succeed in industry, academia, or a research lab. The ability to dive deeper into interesting and challenging topics through research and tailored classes allowed me to grow as an engineer and as a researcher.”

– Ryan Montgomery, UD alumni 2018, Software Engineer at Capital One

“The newly designed Graduate Student Industry Partnership (GSIP) program allows MS students to work directly for the industry with help of mentors from UD. This is a great opportunity to gain working experience while you are still in college.”

– Lavanya Jakka , UD alumni 2018, AirGreen Inc.

Recent Robotics Highlights

Welcome to the

Master of Science in Robotics

The MSR program consists of 30 credit hours of graduate level coursework, and offers a Masters thesis track or a course-based only track. The curriculum consists of a core of six (6) required courses, and four (4) electives. The latter are selected from an approved list of graduate courses and are designed to provide the opportunity for specialization in particular academic subareas such as control, estimation, optimization, or machine learning.

Students interested in our full-time campus experience are able to complete all degree requirements below, including the optional thesis, in as little as 18 to 24 months. See admission requirements and application information below.

Robotics is an interdisciplinary field that requires crossing the boundaries of traditional engineering disciplines. In the face of the rising expenditures on robotics, there will be a continuing and increasing need for skilled interdisciplinary engineers to design, build, and program robots in the future. This interdisciplinary Master of Science in Robotics (MSR) program is answering the societal, government, and industry need for specialized education in this field.

Contact us for more information
Email: msr-info@udel.edu
Phone: 302-831-2423

Click here to apply today

 

Degree Requirements

The program builds on some of the unique strengths, resources, and expertise that can be identified across the University of Delaware campus, to offer a higher education and professional training opportunity that cannot be easily replicated.
Required Courses (18 credits)

Six (6) Required Courses:
MEEG 621 Linear Systems
CISC 621 Algorithm Design and Analysis
MEEG 671 Introduction to Robotics
MEEG 678 Introduction to Autonomous Driving
CISC 642 Introduction to Computer Vision
MAST 632 Environmental Field Robotics

Graduate-Level Engineering Electives (12 credits)

Four (4) graduate-level engineering electives are required. The following courses are pre-approved:
CISC 681 Artificial Intelligence
CISC 684 Introduction to Machine Learning
MEEG 620 Intermediate Dynamics
MEEG 677 Introduction to State Estimation
MEEG 698 Stochastic Optimal Control
MEEG 829 Applied Nonlinear Control
MEEG 877 Sensing and Estimation in Robotics
MEEG 890 Nonlinear Programming
MEEG 894 Linear Feedback Control Design
MEEG 895 Game Theory & Mechanism Design
BMEG 441/667 Biomechatronics
MEEG 467/667 Soft Robots: design, Principles and Applications

Thesis Option

If pursuing the thesis option, two of the electives are substituted for Master’s thesis credits. Graduate-level independent study can substitute for up to six (6) graduate elective credits along a non-thesis degree track. Independent study activities can take place outside the campus, in the context of semester-long internships with approved industry or government partners, but always under the supervision and oversight of a faculty member from the participating academic units, who will be ultimately responsible for assigning a grade for the course.

Through their choice of technical electives, students in the MSR program have the option to select from one of five academic concentrations, each of which involves a set of three related fundamental courses.

Suggested Academic Concentrations (Optional)

We offer five (5) main concentrations, with the following suggested courses:

  1. Control:
    MEEG 621 (Linear Systems); MEEG 698 (Stochastic Optimal Control) or MEEG 894 (Linear Feed-back Control Design); MEEG 829 (Applied Nonlinear Control)
  2. Estimation:
    MEEG 621 (Linear Systems); MEEG 677 (Introduction to State Estimation); MEEG 877 (Sensing and Estimation in Robotics)
  3. Artificial Intelligence:
    CISC 621 (Algorithm Design and Analysis); CISC 684 (Intro to Machine Learning); CISC 642 (Computer Vision)
  4. Design:
    MEEG 620 (Dynamics); MEEG 671 (Intro to Robotics); MAST 632 (Environmental Field Robotics)
  5. Optimization:
    CISC 621 (Algorithms); MEEG 895 (Game Theory and Mechanism Design); MEEG 890 (Nonlinear Programming)

See official program policy statement for details. For more information about this program, contact msr-info@udel.edu

Admission Requirements

The requirements for admission to the MSR program are the following:

  • A baccalaureate degree in mechanical engineering or in a closely allied field of science or mathematics. Applicants with degrees in other disciplines may be admitted with provisional status and may be required to complete prerequisite courses that are deemed necessary for appropriate preparation for courses in the program.
  • An undergraduate grade point average in engineering, science and mathematics courses of at least 3.0 on a 4.0 scale.
  • The Graduate Record Examination (GRE) combined Quantitative and Verbal score of 308 (1200). Waivers may be considered on a case-by-case basis, with documented approval by the Department of Mechanical Engineering’s Admissions Committee.
  • International applicants: The TOEFL with a minimum of 100 on the IBT and a speaking score of 20. IELTS with a minimum score of 6.5 with no individual sub-score below 6.0 on the IELTS alternative.
  • Three letters of recommendation from former teachers or supervisors.
  • Resume
  • Statement of Purpose

All items should be uploaded into your graduate application (https://grad-admissions.udel.edu/apply/). Admission is selective and competitive based on the number of well qualified applicants and the research opportunities available with the faculty. Meeting the stated minimum academic requirements does not guarantee admission.

Application Deadlines

MSR Fall Admission

  • January 31: Priority consideration for admission
  • July 31: Final deadline to apply

MSR Spring Admission

  • October 31: Priority consideration for admission
  • December 31: Final deadline to apply

Tuition rates of all programs can be seen on the Graduate Office’s Tuition webpage.

Contact us for more information
Email: msr-info@udel.edu
Phone: 302-831-2423

Program Core Faculty

Panagiotis (Panos) Artemiadis

Panagiotis (Panos) Artemiadis

Associate Professor & Graduate Program Director

HRI; Rehabilitation
Research Lab

Sambeeta Das

Sambeeta Das

Assistant Professor

Nano/Micro Robotics, Biorobotics
Research Lab

Guoquan Huang

Guoquan Huang

Assistant Professor

Estimation, Machine vision, SLAM
Research Lab

Andreas Malikopoulos

Andreas Malikopoulos

Terri Connor Kelly and John Kelly Career Development Associate Professor

Decentralized Control
Research Lab

Ioannis Poulakakis

Ioannis Poulakakis

Associate Professor

Legged Robots; Nonlinear Control
Research Lab 

Christopher Rasmussen

Christopher Rasmussen

Associate Professor

Computer Vision

Fabrizio Sergi

Fabrizio Sergi

Assistant Professor

Rehabilitation
Research Lab

Herbert Tanner

Herbert Tanner

Professor

Multi-robot Systems; Human-robot Interaction
Research Lab

Arthur Trembanis

Arthur Trembanis

Associate Professor

Oceanography
Research Lab

Affiliated Faculty

Gonzalo Arce

Gonzalo Arce

Professor

Signal Processing

Stephan Bohacek

Stephan Bohacek

Associate Professor

Wireless Networks

Charles Boncelet

Charles Boncelet

Professor

Signal Processing

Austin Brockmeier

Austin Brockmeier

Assistant Professor

Machine Learning, Signal Processing, Neural Engineering
Research Lab

Leonard Cimini

Leonard Cimini

Professor

Networks

Keith Decker

Keith Decker

Associate Professor

Multi-Agent Systems
Research Lab

Jill Higginson

Jill Higginson

Professor

Rehabilitation
Research Lab

Chandra Kambhamettu

Chandra Kambhamettu

Professor

Vision

Mark Moline

Mark Moline

Professor

Marine Science

Xi Peng

Xi Peng

Assistant Professor

Deep Learning; Computer Vision
Research Lab

Thomas Powers

Thomas Powers

Associate Professor

Ethics
Research Lab

Valery Roy

Valery Roy

Associate Professor

Micromechatronics

Vijay Shanker

Vijay Shanker

Professor

Machine Learning

Chien-Chung Shen

Chien-Chung Shen

Professor

Networks

Abhyudai Singh

Abhyudai Singh

Associate Professor

Systems/Synthetic Biology; Stochastic Hybrid Systems
Research Lab

Erin Sparks

Erin Sparks

Assistant Professor

Field-based Robotics; Biomechanics
Research Lab

Adam Wickenheiser

Adam Wickenheiser

Associate Professor

Energy; Environment

Randall Wisser

Randall Wisser

Associate Professor

Plant Science; Quantitative Genetics
Research Lab

Ryan Zurakowski

Ryan Zurakowski

Associate Professor

Mathematical Modeling
Research Lab

Research Labs and Facilities

Students will have the ability to work in state-of-the-art research labs and facilities that are unique in the University of Delaware. Students will be exposed to implementation challenges of turning theory and algorithms into a functional system that is robust enough to be deployed and be functional under real-world conditions. In fact, one of the unique aspects of the MSR program in UD is in leveraging the campus-wide facilities, expertise, and existing faculty collaborations, to expose its students within the normal curriculum, to aspects of implementation and utilization of robotic systems in air, land, and sea.

Areas of Research Interest Include:

  • HRI
  • Rehabilitation
  • Wireless Networks
  • Signal Processing
  • Machine Learning
  • Signal Processing
  • Neural Engineering
  • Networks
  • Nano/Micro Robotics
  • Biorobotics
  • Multi-agent Systems
  • Rehabilitation
  • Estimation Machine Vision
  • SLAM
  • Vision
  • Decentralized Control
  • Marine Science
  • Deep Learning
  • Computer Vision
  • Legged Robots
  • Nonlinear Control
  • Ethics
  • Computer Vision
  • Micromechatronics
  • Rehabilitation
  • Machine Learning
  • Networks
  • Systems/Synthetic Biology
  • Stochastic Hybrid Systems
  • Field-based Robotics
  • Biomechanics
  • Multi-robot Systems
  • Human-robot Interaction
  • Oceanography
  • Energy
  • Environment
  • Plant Science
  • Quantitative Genetics
  • Mathematical Modeling
  • Brain machine interfaces
  • Swarm robotics
  • Human-Swarm Interaction

Recent Robotics Highlights

Academics Graduate Programs Master of Science in Robotics (MSR)