To earn a Master of Science in Mechatronics and Robotics degree at the School of Engineering, you must complete 30 credits as outlined below. At least 6 credits will be fulfilled through your chosen specialty.
Required Courses
- Mechatronics ROB-GY 5103
- Introduction to theoretical and applied mechatronics, design and operation of mechatronics systems; mechanical, electrical, electronic, and opto-electronic components; sensors and actuators including signal conditioning and power electronics; microcontrollers—fundamentals, programming, and interfacing; and feedback control. Includes structured and term projects in the design and development of proto-type integrated mechatronic systems.
Prerequisite: Graduate standing or advisor approval
- Foundations of Robotics ROB-GY 6003
- This course presents the concepts, techniques, algorithms, and state-of-the-art approaches for mobile robots and robot manipulators covering modeling, control and simulation. The class will focus on direct and inverse kinematics problem, Denavit-Hartenberg representation, Euler and RPY angles, homogeneous transformations, Manipulator Jacobian, differential relationships, force and moment analysis, inverse Jacobian, trajectory generation and path planning. The final part will involve robot arm dynamics and PD and PID controllers for robotic manipulators, practical robotic system implementation aspects, limitations and constraints, and sensors and actuators. The students will practice these concepts using Matlab or an equivalent simulation environment.
Prerequisite: Graduate standing or advisor approval
- Mathematics for Robotics ROB-GY 6013
- The student who completes this course will gain a fundamental understanding of the principles underlying mathematics and numerical methods for dynamical systems, with particular reference to robotic systems. He/she will be able to use mathematical tools and computational methods for formulating and solving the modeling, estimation, planning, optimization, and control problems related to robotic systems. The course will employ real-world robotics examples throughout the introduction to and applications of mathematical, numerical and simulation approaches.
Prerequisite: Graduate standing or advisor approval
- Advanced Mechatronics ROB-GY 6103
- Introduction to, applications of, and hands-on experience with microcontrollers and single-board computers for embedded system applications. Specifically, gain familiarity with the fundamentals, anatomy, functionality, programming, interfacing, and protocols for the Arduino microcontroller, multi-core Propeller microcontroller, and single-board computer Raspberry Pi. Includes mini-projects and term projects in the design and development of proto-type integrated mechatronic systems.
Prerequisite: Graduate standing and ROB-GY 5103 or advisor approval
- Entrepreneurship MG-GY 7703
- This course focuses on entrepreneurship and venture creation as key engines for wealth creation and successful business strategy in the modern, innovation-intensive, high-tech economy. The course deals with key issues such as: (1) assessing attractiveness of opportunities; (2) launching a new venture; (3) nurturing, growing and entrepreneurial venture; (4) obtaining the necessary financial, human and technology resources; (5) managing the transition from a small entrepreneurial firm to a large, sustainable, professionally managed but still entrepreneurial corporation; and (6) being an entrepreneur and promoting entrepreneurship in a large corporation.
ROB-GY xxxx Required for Specialty Area, Credits: 6.00 total
ME-GY xxxx Project (ME-GY 9963) or Thesis (ME-GY 9973) Approved by Research Advisor, Credits: 6.00 total
Free Electives, Credits: 3.00 total
Free elective suggestions: MG-GY 7743 Advanced Trends in Technology Management & Innovation; MG-GY 7861 High-Technology Entrepreneurship; MG-GY 7871 Introduction to Managing Intellectual Property; MG-GY 8653 Managing Technological Change & Innovation.
Specialty
Two courses from the same specialty area must be taken from the following list to develop a specialization
Assistive mechatronic and robotic technologies
- Robots for Disability ROB-GY 6413
- This course will introduce personal, societal, and technological challenges related to physical disability, cognitive disability, and senior living. After an introduction to these challenges, students will learn about current state of art mechatronics and robotics solutions to handle these problems. Finally, they will apply their mechatronics and robotics learning to produce novel robotics solutions to address a specific problem related to a disability.
Prerequisite: Graduate standing and ROB-GY 5103 or advisor approval
- Gait and Manipulation ROB-GY 6313
- Review of fundamental robot kinematics, dynamics, and control. Types of robotic manipulation. Design and control of robotic manipulators. Robotic hand and arm. Robotic manipulation modeling, simulation, and experiments. Gait types of legged systems. Biped and quadruped systems. Human walking and running, and passive dynamics. Design and control of biped walking robots. Robotic gait modeling, simulation, and experiments. Focus on hands-on experience in design, fabrication, and control of simple mechanisms.
Prerequisite: Graduate standing and ROB-GY 6003 or advisor approval
- Interactive Medical Robotics ROB-GY 6423
- In this course, we will investigate the application, functionality, and theoretical aspects of the state-of-the-art interactive robotic technologies in medicine. The focus of the course will be on advanced surgical, and neurorehabilitative robotic systems. Technological aspects, such as instrumentation, actuation, mechanisms, imaging, and signal acquisition, will be introduced. Also, theoretical aspects related to control, dynamics, kinematics, haptics, stability, passivity, human-robot interaction, teleoperation, machine learning and bio-signal processing will be discussed in the context of medical robotic systems. Students are expected to be fluent in MATLAB and have solid background in at least two of the following four topics: signal processing, dynamics, control, robotics.
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Prerequisite: Graduate standing and ME-GY 6703 or ROB-GY 6003 or advisor approval
Mobile robotics
- Robot Localization and Navigation ROB-GY 6213
- This course presents the concepts, techniques, algorithms, and state-of-the-art approaches for robot perception, localization, and mapping. The course will show the theoretical foundations and will also have a substantial experimental component based on Matlab/ROS. The course will start from basic concepts in probability and then introduce probabilistic approaches for data fusion such as Bayes Filters, Kalman Filter, Extended Kalman Filter, Unscented Kalman Filter, and Particle Filter. Then, the course will introduce the SLAM problem showing how this has recently been solved using batch optimization and graph methods. Finally, mapping algorithms will also be briefly discussed.
Prerequisite: Graduate standing and ME-GY 6923 or ME-GY 6703 or advisor approval
- Swarm Robotics ROB-GY 6333
- The student who completes this course will gain an advanced understanding of the analysis and control of networked dynamical systems, with a specific accent on networked robotic systems. He/she will be able to study the properties of networked robotic systems through the analysis of the intertwining properties of the network structure and of the individual dynamics of the single robot. Moreover, he/she will be able to understand and design algorithms for distributed control of teams of mobile agents and robots.
Prerequisite: Graduate standing and ME-GY 6703 or ROB-GY 6003 or advisor approval
- Reinforcement Learning and Optimal Control for Robotics ROB-GY 6323
- What kind of movements should a robot perform in order to walk, jump or manipulate objects? Can it compute optimal behaviors online? Can it learn this directly from trial and error? This course will introduce modern methods for robotics movement generation based on numerical optimal control and reinforcement learning. It will cover fundamental topics in numerical optimal control (Bellman equations, differential dynamic programming, model predictive control) and reinforcement learning (actor-critic algorithms, model-based reinforcement learning, deep reinforcement learning) applied to robotics. It will also contain hands-on exercises for real robotic applications such as walking and jumping, object manipulation or acrobatic drones. Recommended background in at least one of the following: linear systems; robotics; machine learning; convex optimization; programming (python).
Prerequisite: Graduate standing and ME-GY 6703 or ROB-GY 6003 or advisor approval
- Robot Perception ROB-GY 6203
- Smart automation systems (e.g., driverless cars, domestic/warehouse mobile robots, intelligent transportation systems, robotic construction machines, etc.) need to understand both their own poses and the surroundings to fulfil their tasks safely, accurately, and efficiently. This requires an intelligent extraction of both geometric and semantic information from sensory input (mainly visual sensors such as cameras/LIDAR). This course aims to combine the established theories of geometric vision and the recent progress in pattern recognition in the context of robotic/intelligent systems. Students will study and practice the basic theories of computer vision and machine learning through relevant applications. For example, pose estimation of a robotic agent from onboard cameras, 3D reconstruction for map creation, object detection/segmentation for obstacle avoidance, tracking for target following, place recognition from images when GPS is unreliable, and so on.
Prerequisite: Graduate standing or advisor approval
- MS Project ME-GY 996X
- This course is an engineering project under faculty guidance. A written project proposal and final report must be submitted to the department head and the adviser and may be extended to a thesis with the project advisor’s recommendation. Credit only upon completion of project.
- MS Thesis ME-GY 997X
- The master’s thesis presents results of original investigation in the student’s specialty. This effort can be an extension of ME-GY 9963, with approval of the project adviser. Continuous registration is required. Maximum of 9 credits of ME-GY 996X/ME-GY 997X are counted toward the degree.
- Curricular Practical Training ME-GY ---X
Important Credit and Course Notes
- To graduate, you must have a 3.0 GPA or better in each of the following:
- In the average of all graduate courses taken at the School of Engineering (whether or not some of these courses are being used to satisfy specific degree requirements)
- In the average of all courses submitted for the graduate degree
- In each guided studies, readings, projects, thesis, courses, or credits enrolled
- You must take at least 21 credits out of the 30 credits needed for the degree at the School of Engineering. In other words, 9 credits may be transferred from elsewhere.
- No more than 6 credits in “Guided Reading” courses are allowed
- Validation credit is not allowed, but the graduate adviser may waive specific requirements (and substitute designated ones), based upon your prior studies or experience
- Transfer credits are not granted for the following:
- Undergraduate courses
- Courses counted toward satisfying undergraduate degree requirements
- Courses not related to the graduate program as stated in this catalog
- Courses that received a grade lower than B
- You must complete your degree in 5 years, unless a formal leave of absence is approved before the period for which studies are interrupted
- If you decide to do a ME-GY 9973 Master Thesis for 9 credits as part of your work for the degree, 3 out of the 9 credits will be counted against the 3 credits of Free Electives.
- You are not allowed to submit more than 3 courses (9 credits), starting with a 5 for MS degree requirements satisfaction
- Departmental electives include courses with a robotics (ROB), mechanical (ME), aerospace (AE), or materials (MT) prefix, plus departmental thesis or project credits
- All courses and program details are subject to adviser approval
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