Education

Master's In Robotics

 

The modern expert in robotics and intelligent systems must be proficient in artificial intelligence, computer vision, control systems, dynamics, machine learning, as well as the design, programming, and prototyping of robotic systems. Such subjects typically reside in different departments, and departmental programs do not offer the flexibility for cross-departmental training. The Robotics Master of Science In Engineering (M.S.E.) program offers a more balanced and flexible academic curriculum that cuts across multiple departments. 

Please go to www.cis.upenn.edu/grad/applications.shtml to access application information. Applicants to the Master of Science in Robotics program are expected to have a strong academic background in computer science, electrical engineering, or mechanical engineering.

Academic Curriculum
The Robotics M.S.E. requirements consist of a total of ten courses, including an optional thesis project.

Courses:
Students are required to take courses in at least three of the four foundational areas: Artificial Intelligence, Mechanism Design and Analysis, Perception and Control. The list below indicates the foundational courses in each of these four areas.
Note: Students are allowed and in fact encouraged to take more than three courses from this list. These additional courses can be counted as Technical Electives or as General Electives.

Students are required to take at least 5 courses from the list of Technical Electives. Students are allowed 2 General Elective courses which can be taken from any technical field (egs. Mathematics, Computer Science, Electrical and Systems Engineering or Mechanical Engineering). Courses in other disciplines may be used as General Electives with the approval of the Robotics Program Director.

Foundational Courses (at least 3)

Artificial Intelligence:

  • CIS 520 Machine Learning
  • CIS 521 Fundamentals of AI
  • ESE 650 Learning in Robotics


Robot Design and Analysis:

  • MEAM 510 Design of Mechatronic Systems
  • MEAM 520 Introduction to Robotics
  • MEAM 620 Advanced Robotics


Control:

  • ESE 500 Linear Systems
  • ESE 505/MEAM 513 Control Systems Design


Perception:

  • CIS 580 Machine Perception
  • CIS 581 Computer Vision & Computational Photography


Technical Elective Courses (at least 5)

  • BE 521 Brain-Computer Interfaces
  • CIS 502 Analysis of Algorithms
  • CIS 510 Curves & Surfaces: Theory & Applications
  • CIS 511 Theory of Computation
  • CIS 520 Machine Learning
  • CIS 521 Fundamentals of AI
  • CIS 530 Computational Linguistics
  • CIS 540 Principles of Embedded Computation
  • CIS 541 Embedded Software for Life-Critical Applications
  • CIS 560 Computer Graphics
  • CIS 562 Computer Animation
  • CIS 563 Physically Based Animation
  • CIS 564 Game Design & Development 
  • CIS 565 GPU Programming & Architecture
  • CIS 580 Machine Perception
  • CIS 581 Computer Vision & Computational Photography
  • CIS 610 Advanced Geometric Methods
  • CIS 620 Advanced Topics in AI
  • CIS 680 Vision and Learning
  • ENM 502 Numerical Methods & Modeling
  • ENM 503 Introduction to Probability & Statistics
  • ENM 510 Foundations of Engineering Math I
  • ENM 511 Foundations of Engineering Math II
  • ESE 500 Linear Systems
  • ESE 504 Introduction to Optimization
  • ESE 505/MEAM 513 Control Systems Design
  • ESE 519 Real Time & Embedded Systems
  • ESE 530 Elements of Probability Theory & Random Processes
  • ESE 601 Hybrid Systems
  • ESE 605 Convex Optimization
  • ESE 617 Nonlinear Systems
  • ESE 650 Learning in Robotics
  • ESE 680 Dynamic Programming - Special Topics in ESE
  • IPD 501 Integrated Computer-Aided Design, Manufacturing & Analysis
  • IPD 511 Creative Thinking & Functional Iteration in Design
  • IPD 515 Product Design (formerly MEAM 515)
  • MEAM 510 Design of Mechatronic Systems
  • MEAM 513/ESE 505 Control Systems Design
  • MEAM 516 Advanced Mechatronic Reactive Spaces
  • MEAM 520 Introduction to Robotics
  • MEAM 535 Advanced Dynamics
  • MEAM 545 Aerodynamics
  • MEAM 620 Robotics
  • MEAM 625 Haptic Interfaces
  • PSYC 719 Experimental Methods in Perception
  • ESE/CIS/MEAM 599 Masters Independent Study (Note: Only one Independent Study may be taken for the degree)
  • ESE/CIS/MEAM 597 Masters Thesis Research (Click here for masters thesis requirements.) 

General Elective Courses (at most 2)
Graduate level courses in Mathematics, Computer Science, Electrical Engineering or Mechanical Engineering. Students can also use any of the foundational or technical elective courses listed above as general electives.
Courses in other disciplines may be used with the approval of the Robotics Program Director.

The following courses may also be used as General Electives...

  • EAS 545 Engineering Entrepreneurship I
  • EAS 546 Engineering Entrepreneurship II
  • ESE 540 Engineering Economics

Course Schedule Information:
(Note: Use the following links to view detailed course schedule information)

 

GENERAL INFORMATION

Course Descriptions:

Registration procedures    


Payment Information:

 

ADVISING -

Students are assigned an academic advisor from the distinguished members of the GRASP faculty. Applicants are encouraged to indicate a potential academic advisor in the personal statement section of the application. A program of study is developed with the academic advisor, who is responsible for monitoring the student's academic plan and thesis work; the thesis supervisor will be typically the academic advisor.

THESIS -

Students may pursue research and write an M.S.E thesis on a suitable topic under the supervision of a GRASP faculty member (usually but not necessarily their academic advisor). The findings of the thesis should be made as a verbal presentation to the members of GRASP Lab. The thesis must be prepared and submitted following the SEAS and University of Pennsylvania requirements as outlined at www.upenn.edu/VPGE/masters.html.  The student's advisor and the Robotics master's program director, will make the final approval of the thesis.  Registration for two masters thesis credits counts towards two of the technical elective requirements. 

More resources at CIS Grad web page -  www.cis.upenn.edu/grad/

Questions - charity@cis.upenn.edu