Information for Current Master's Students

The Robotics M.S.E. requirements consist of a total of ten courses, including an optional thesis project. Graduate students in all study areas will find a broad range of multidisciplinary courses to choose from.

 

Resources for Incoming Master's Students
 


Overview

Students are required to take courses in at least three of the four foundational areas: Artificial Intelligence, Mechanism Design and Analysis, Perception and Control.

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 pre-approval of the Robotics Program Director.

Robotics MicroMasters Cerficate

Please note that current students are not eligible to use the Robotics MicroMasters certificate towards their degree.


Courses

Foundational Courses (at least 3):

Artificial Intelligence:

  • CIS 519 Introduction to Machine Learning
  • 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 515 Foundations of Linear Algebra & Optimization
  • CIS 519 Introduction to Machine Learning
  • CIS 520 Machine Learning
  • CIS 521 Fundamentals of AI
  • CIS 526 Machine Translation
  • 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
  • CIS 700 Integrated Intelligence for Robotics (*other topics considered a general elective for ROBO)
  • CIS 700 Topics in Machine Perception (*other topics considered a general elective for ROBO)
  • 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
  • ENM 520 Principles and Techniques of Applied Math I
  • ENM 521 Principles and Techniques of Applied 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 531 Digital Signal Processing
  • ESE 601 Hybrid Systems
  • ESE 605 Convex Optimization
  • ESE 617 Nonlinear Systems
  • ESE 619 Model Predictive Control
  • ESE 650 Learning in Robotics
  • ESE 680 Dynamic Programming (*other topics considered a general elective for ROBO)
  • IPD 501 Integrated Computer-Aided Design, Manufacturing & Analysis
  • 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 517 Control and Optimization with Applications in Robotics
  • MEAM 520 Introduction to Robotics
  • MEAM 535 Advanced Dynamics
  • MEAM 543 Performance and Design of Unmanned Aerial Vehicles (UAVs)
  • MEAM 545 Aerodynamics
  • MEAM 620 Robotics
  • MEAM 625 Haptic Interfaces
  • PSYC 579 Experimental Methods in Perception
  • ROBO 599 (ESE/CIS/MEAM 599 for older students starting before Fall 2014) *Masters Independent Study (Note: Only one Independent Study may be taken for the degree)
  • ROBO 597 (ESE/CIS/MEAM 599 for students starting before Fall 2014) *Masters Thesis Research (Click here for masters thesis requirements.)

* See Approval forms below

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. The courses listed below will only be considered as general electives for the Robotics Master's course requirements.

  • CIS 505 Software Systems
  • CIS 700 Special Topic (Not listed Specifically Above)
  • EAS 545 Engineering Entrepreneurship I
  • EAS 546 Engineering Entrepreneurship II
  • ESE 540 Engineering Economics 
  • ESE 543 Human Systems Engineering
  • ESE 680 Special Topic (Not listed Specifically Above)
  • IPD 504/BE 514 Rehab Engineering and Design
  • IPD 511 Creative Thinking & Functional Iteration in Design
  • IPD 514 (MEAM514) Design for Manufacturability
  • IPD 525 Ergonomics/Human Factors Based Product Design
  • IPD 527 (ARCH727) Industrial Design I
  • PHIL 530 Philosophy of Artificial Intelligence

Courses in other disciplines may be used with the pre-approval of the Robotics Program Director. Approval of a course is NOT guaranteed.

Course schedule information:


General Information

Course Descriptions:

Registration Procedures:

Payment Information:

Estimated Tuition/Fees
Student Financial Services   
Billing information & billing schedule (Note: The University begins billing shortly after registration and late fees may be incurred)


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 here.

Here are some additional resources:

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 graduate student resources are available here - http://www.seas.upenn.edu/graduate/advising/index.php

Questions - charity@cis.upenn.edu


Forms for Current Students