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.
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.
Students must complete a total of 5 pre-approved Technical Electives (12 units each; 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.
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.
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.
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.
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.
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.
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
Title: Computer Vision: A Modern Approach
Authors: David Forsyth and Jean Ponce
Publisher: Prentice Hall
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.
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.
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 in their summer semester. The intent will be to allow them to put into practice what they have learned, and report back on the combination of technical and business / management / finance aspects of their internship, in the following Fall semester. 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).
The internship is scheduled to run from June through August after the completion of the 2nd semester, allowing students sufficient time to return to campus and start their 3rd and final Fall semester.