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MRSD Program Curriculum
    The degree requirements for students in the Master of Science - Robotics Systems Development (MRSD) Program at Carnegie Mellon consist of Robotics / Automation Project Courses, and Business / Management and Technical Mini-Courses. The MRSD curriculum is composed of a three-semester teaching portion (9 months) and an optional industrial internship / practicum (3 months in the summer), resulting in a 16-month long program. Students are permitted to take up to 12 units of advanced undergraduate level (i.e. XX-300/XX-400) coursework. Students must complete 162 units of coursework to be eligible for graduation.

    Each of the first two semesters consists of two core-courses and an elective course, as well as a project course and business/management seminars. Note that all technical-content courses are based on materials (lectures, notes, assignments, labs, etc.) compiled from various existing courses already taught by RI faculty for the existing M.Sc. and Ph.D. degree students, and upgraded in content to reflect the more applied, practical and hands-on focus of the MRSD degree:

    • 1st Semester - 1st Fall Term:
      • 1st core course: Systems Engineering and Management for Robotics
      • 2nd core course: Manipulation, Mobility & Control
      • One Technical Elective
    • One Project Course: MRSD Project I
    • One Business Course: MRSD Seminar I

  • 2nd Semester - Spring Term:
    • 3rd core course: Computer Vision.
    • 4th core course: Robot Autonomy.
    • One Technical Elective
  • One Project Course: MRSD Project II
  • One Business Course: MRSD Seminar II
  • Summer Term:
    • Optional Internship with a technical company (3 units)
  • 3rd Semester - 2nd Fall Term:
    • Three Technical Electives
    • One Business Elective

    The matrix of courses, deliverables (exams, presentations, demonstrations, etc.) for the Fall 2015 incoming class are as shown in the figure below. Detailed course descriptions are also shown, and will be updated as they become available. Note that the number of units listed for each course, is meant to provide a guideline of the number of hours spent on each course in a given week; however, this number is meant purely as a guide. Many times students have spent far more time on researching the background materials, meeting in team-settings, doing homework and/or lab work, depending on their background and complexity and breadth/depth of the project or solution being implemented.


    • XX-xxx – Business Elective(s)

    Students are required to complete 12 units of Business Electives during the 3rd and final semester in order to be eligible for graduation. Business Electives (subject to availability and School / Faculty approval) may be chosen from the Tepper School of Business or the Heinz College. Many of the courses offered by Tepper and Heinz are “mini” courses. Mini courses are 6 units and last one-half of a semester. Students will need to complete either one 12 unit course or two 6 unit mini courses to meet the Business Elective requirement.

    Business Elective are selected from a pre-approved list that is distributed to the students each semester by the MRSD Program Administrator.

    • XX-xxx – 5 Technical Electives

    Students must complete a total of 5 pre-approved Technical Electives (60 units total) to be eligible for graduation. Students are required to take a total of 2 Technical Electives by the end of the first year of study (Fall and Spring). Depending on the level of proficiency of individual students, the MRSD Program Director may require that certain incoming students be directed to subscribe to a Math-Fundamentals course as a 1st semester elective.In the 3rd and final semester, students are required to register for 3 Technical Electives. Students who obtain a MRSD relevant summer internship will earn 3 units that will be counted towards the Technical Elective requirement. This allows flexibility to complete one 9 unit Technical Elective. Students who do not obtain a MRSD relevant summer internship will meet the Technical Elective requirement through 60 units (i.e. five 12 unit courses) of formal coursework.

  • Students must enroll for a minimum of 4 Technical Electives offered by the School of Computer Science (SCS).
      • 2 of the SCS Technical Electives must be Robotics Institute Courses (16-xxx)
      • The 2 remaining SCS Technical Electives must be pre-approved courses from any SCS Department (02-xxx, 05-xxx, 08-xxx, 10-xxx, 11-xxx, 15-xxx, 16-xxx, 17-xxx)
  • A maximum of 1 Technical Elective taken during the 3rd semester may be a pre-approved course from the College of Engineering (06-xxx, 12-xxx, 18-xxx, 19-xxx, 24-xxx, 27-xxx, 39-xxx, 42-xxx) or the School of Computer Science (see xx-xxx, above).

    The technical electives listed below are pre-approved for the MRSD Program and do not require permission from the Program Director. If you find an MRSD relevant course that is not included on this list please send the course name, number and description to the MRSD Program Administrator for review and approval.

    • Pre-approved Technical Electives:
        • 02-513 – Algorithms and Data Structures for Scientists
        • 05-651 – Interaction Design Fundamentals
        • 05-818 – Design Educational Games
        • 05-831 – Human Factors
        • 05-833 – Gadgets, Sensors and Activity Recognition in HCI
        • 05-834 – Applied Machine Learning
        • 08-722 – Data Structures for Application Programmers
        • 10-601 – Machine Learning
        • 10-605 – Special Topics in Machine Learning and Policy
        • 10-701 – Machine Learning
        • 10-704 – Information Processing and Learning
        • 11-755 – Machine Learning for Signal Processing
        • 11-611 – Natural Language Processing
        • 11-663 – Applied Machine Learning
        • 15-351/650 – Algorithms and Advanced Data Structures
        • 15-415/615 – Database Applications
        • 15-451/651 – Algorithm Design and Analysis
        • 15-491 – CMRobobits – Creating Intelligent Robots
        • 15-619 – Cloud Computing
        • 15-640 – Distributed Systems
        • 15-663 – Computational Photography
        • 15-780 – Artificial Intelligence
        • 15-887 – Planning Execution and Learning
        • 15-889E – Advanced Topics in Artificial Intelligence
        • 16-362 – Mobile Robot Programming Laboratory
        • 16-384 – Robot Kinematics and Dynamics
        • 16-423 – Designing Computer Vision Apps
        • 16-467 – Human Robot Interaction
        • 16-711 – Kinematics, Dynamic Systems and Control
        • 16-722 – Sensing and Sensors
        • 16-725 – Methods in Medical Image Analysis
        • 16-741 – Mechanics of Manipulation
        • 16-761 – Mobile Robots
        • 16-811 – Mathematical Fundamentals for Robotics
        • 16-822 – Geometry-based Methods in Vision
        • 16-831 – Statistical Techniques in Robotics
        • 16-861 – Mobile Robot Design
        • 16-867 – Principles of Human Robot Interaction
        • 16-868 – Biomechanics & Motor Control
        • 17-630 – Computer Science for Practicing Engineers
        • 17-653 – Managing Software Development
        • 17-655 – Architectures for Software Systems
        • 18-640 – Foundations of Computer Architecture
        • 18-642 – Introduction to Software Engineering
        • 18-649 – Distributed Embedded Systems
        • 18-667 – Design of Integrated Embedded Systems
        • 18-777 – Complex Large-Scale Dynamic Systems
        • 24-614 – Microelectromechanical Systems
        • 24-651 – Special Topics in Material Selection for Mechanical Engineers
        • 24-671 – Special Topics – Practical Control and Automation
        • 24-672 – Special Topics in DIY Design and Fabrication
        • 24-673 – Soft Robots: Mechanics, Design and Modeling
        • 24-674 – Design of Biomechatronic Systems for Humans
        • 24-677 – Special Topics: Aerial Robotics
        • 24-683 – Design for Manufacture and the Environment
        • 24-787 – Artificial Intelligence and Machine Learning for Engineering Design
        • 51-763 – Industrial Design Fundamentals

    • 16-650 – Systems Engineering and Management for Robotics
    This course consists of 2 parts: In the first part we study the fundamentals of systems engineering as they apply to the development of robotic systems. Systems Engineering is a formal discipline that guides a product from conception and design all the way to production, marketing, servicing, and disposal. The higher the complexity of the system, the more its creators benefit from applying formal processes such as Systems Engineering to its development. Topics in Systems Engineering covered in this course include needs and objectives analysis, requirements elicitation and formalization, system architecture development, trade studies, verification and validation, structured methodologies, etc. In the second part of this course we study key concepts in Project Management that must be performed along with Systems Engineering to achieve a successful project and product in a finite time period. For the Project Management portion of the course we cover topics such as work breakdown structures, scheduling, estimation, risk management, and agile methods. The students apply the concepts and methods they learn in this course to the MRSD Project courses I and II, thus giving them the opportunity to put the theory in practice in a requirements-driven robotic system development.

    • 16-642 – Manipulation, Mobility & Control

    This course provides an overview of the current techniques that allow robots to locomote and interact with the world. The kinematics and dynamics of electromechanical systems will be covered with a particular focus on their application to robotic arms. Some basic principles of robot control will be discussed, ranging from independent- joint PID tracking to coupled computed torque approaches. The practice and theory of robotic mobility will be investigated through various mobile robot platforms, including wheeled and tracked vehicle and legged robots. Hands-on experience with some of the topics in the class will be provided through practical demonstrations and lab assignments.

    • 16-681 & 16-682 – MRSD Project I & II

    Students will be required to participate in a two-semester on-campus lecture- and laboratory-style project course. The project course will allow students to form project teams to work on a hands-on robotics / automation topic proposed by the instructor(s) of interest to the robotics / automation industry at large. The project is intended to allow students to acquire hands-on experience and apply concepts and methods taught in class. Students will learn the interconnection of theory and practice and understand the challenges of real-world application. The setting will consist of a mix of targeted technology instruction / lectures and hands-on work in the laboratory. Students will be taught the project / technology development process all the way from developing performance-requirements/system-specifications through the technology development cycle, all the way to test-plan development and results analysis and reporting. The outcome of this two-semester course will be a final project report, coupled with a demonstration and group presentation.

    The goal of the MRSD Project Course is to provide practical experience in robotic system development ranging from specification and design to implementation and testing. Projects will be defined jointly with industrial clients, and small student teams will work with these client companies in implementing, refining, and presenting the results of their projects. The course will provide opportunities to apply principles from other MRSD courses, especially the Systems Engineering course, as well as those from the Business Seminar series. Class lectures will emphasize practical application and cover relevant topics including robotic design methodologies, system modeling, mechanical components, sensor and I/O interfacing, motor control, microcontroller and embedded control basics, basic software development methodologies, and troubleshooting. Early laboratory assignments will involve mastering these basics; later laboratory work will focus on applying the skills learned to building, integrating, testing, and iteratively refining the final projects. Student teams will have regular design reviews and other presentations of their work in various forms and forums.

    Examples of past robot system projects developed by previous teams of MRSD students can be found here.

    • 16-697 & 16-698 – MRSD Business Seminar I & II

    Students will be required to participate in a two-semester on-campus seminar-style lecture and team-project class. These two mini-courses will cover technical, business, management, finance, production, marketing & sales and writing / presentation topics at a broad yet deep enough level, to allow students to participate in individual teams towards the creation of a Technology Development Plan (TDP; akin to a Business Plan with less emphasis on detailed monthly cash-flow). Speakers from academia (technical, business) and industry (production, case-studies, etc.) will cover a myriad number of topics to provide students the foundation to be able to compose a TDP. The Technology Plan is expected to cover all aspects required by a company to define a new product development: analyze the competition and market opportunity, detail the envisioned product, lay out the development path and its required resources (personnel, facilities, hardware, etc.), plan out (time, resources & cost) the production-readiness activities, develop costing and pricing models and develop a marketing and sales plan for the product introduction. All these elements will form part of the TDP, which will be submitted as a final report and orally presented by the team to the class / faculty at the conclusion of the two-semester course.

    The course will be taught using a weekly lecture series. The format of the lectures will be based on the coverage of key topics of importance to understanding the connections between technology (design, development, etc.), management (leadership, teaming, negotiations, etc.) and business (finance, etc.), marketing/sales, intellectual property protection and manufacturing and pricing. Students will be expected to form development teams and have out-of-class team-meetings to self-organize themselves and work on their joint TDP.

    • The course syllabus includes lectures in the areas of:
        • Computer Tools
        • Communication Skills
        • Leadership, Interpersonal Management & Organizations
        • Business Opportunity Analysis & Feasibility
        • Innovation Management
        • Product Design & Development
        • Project Planning & Management
        • Financial Modeling
        • Marketing & Sales
        • Production, Operations & Supply Management
        • Industrial Case Studies

    Students will be expected to create teams and develop a TDP. Students will be encouraged to link their TDP to the project being targeted in the MRSD Project Course, where systematic design / development and hands-on activities are being targeted. Each semester will conclude with a presentation of their TDP-status and any related results/proof from their MRSD Project Course to support their conclusions.

    The course will be letter-graded and a passing-grade threshold will be set by the course instructor. This course will be lead by the MRSD Program Director and co-taught by multiple faculty from CMU’s Tepper Business School, outside industry experts and consultants.

    • 16-720 – Computer Vision

    This course introduces the fundamental techniques used in computer vision, that is, the analysis of patterns in visual images to reconstruct and understand the objects and scenes that generated them. Topics covered include image formation and representation, camera geometry and calibration, multi-view geometry, stereo, 3D reconstruction from images, motion analysis, image segmentation, object recognition. The material is based on graduate-level texts augmented with research papers, as appropriate. Evaluation is based on homeworks and final project. The homeworks involve considerable Matlab programming exercises.

    Texts recommended but not required:

    Title: Computer Vision Algorithms and Applications
    Series: Texts in Computer Science
    Author: Richard Szeliski
    Publisher: Springer
    ISBN: 978-1-84882-934-3

    Title: Computer Vision: A Modern Approach
    Authors: David Forsyth and Jean Ponce
    Publisher: Prentice Hall
    ISBN: 0-13-085198-1

    This course is taught by a Sr. faculty member in the School of Computer Science (SCS) in both the Fall (M. Hebert) and Spring (S. Narasimhan) semesters. Details pertaining to the course can be found on the RI VASC website.

    • 16-662 – Robot Autonomy

    Robot autonomy delves into the interplay between perception, manipulation, navigation, and learning required to develop fully autonomous systems. We will focus on application domains like the home, retail, and healthcare and identify common themes and key bottlenecks. We will discuss the state of the art algorithms, their computational and hardware requirements, and their limitations. An end-to-end system often requires mixing and matching various algorithms and you will learn some tried and true methods for making systematic decisions. You will learn how to address clutter and uncertainty in manipulation tasks, develop robust object recognition algorithms in real-world scenes, navigate safely in human spaces, and build behavior engines for high-level tasks, among many other things.

    You will also exercise your learning on a real-world mobile dual-arm manipulation platform in your class project, demonstrating robot autonomy.More details on the course can be found here.

    Examples of past robot autonomy projects carried out by previous teams of MRSD students can be found here.

    Students will be encouraged (but are not required) to carry out a 3-month optional summer internship during the summer between the 2nd and 3rd semester. The intent is to allow students to put into practice what they have learned, and report back on the combination of technical and business / management / finance aspects of their internship. The internship may be carried out at a partnering industrial company (or government / for-profit R&D facility). Earlier in the 1st Fall semester, participating companies / laboratories will provide brief overviews of their companies and products / activities, to allow students to form an impression of their choice internship companies. The MRSD will match students to companies using a simple ‘pairing’ process, which will include students being asked to list their 1st-thru-10th choice with companies professing preferences in terms of specialties/backgrounds for interns, which the MRSD Program Office will use to carry out a marriage/matching process, which will include résumé-book publishing, company-instigated/-led interviews, etc. Once student and company are ‘matched’, the student and company are left to negotiate the terms of the internship as a separate and standalone employment agreement subject to the company's terms.

    The MRSD Program Director and each of the companies will work out, and agree on, a potential list of topics/areas or even specific projects, that the interns would be matched to as part of the internship period in their degree program. This will be a critical step to ensure that the internship is of the appropriate level, scope and training-level for the student, as well as of utility, value and potential for the industrial employer. Individual companies will be encouraged further to develop clear internship project goals with the MRSD Program Director, which students will be expected to work on during their internship. Internships in foreign robotics / automation companies are possible, yet need to be approved by the MRSD Program Director up-front. Foreign students wishing to intern at a company in the U.S., will have to apply for, and be granted, their Curricular Practical Training (CPT; different and separate to the OPT) authorization, prior to beginning their internship in the U.S. (precludes ITAR-limitations).

    Students choosing to complete a MRSD relevant summer internship will be registered for 3 units of 16-991 "Internship". The 3 units are counted towards the Technical Elective requirement and will factor into the 162 unit total required for graduation (thus allowing students who complete an internship the flexibility to take a 9 unit Technical Elective). Internships are expected to fall within the summer term as outlined by the University Academic Calendar. Interns will be required to submit a final end-of-internship report documenting the work that they carried out as part of their internship. The MRSD Program Director will review the reports and assign a Pass/Fail grade at the end of the summer term.