Robotics and Autonomous Systems Minor
Robotics and Autonomous Systems (RAS) is believed to be one of the transformative technologies for several key fields including healthcare, manufacturing and public safety in the United States. As we know, restructuring of US manufacturing is essential to the future of economic growth and the creation of new jobs and ensuring competitiveness of US industry. However, due to a shortfall of investment of robotics research in the past decades, the US is losing leadership in this area. As a result, industry has found difficulty in hiring high quality employees in the robotics and automation field. Resurgence of RAS has been fueled by recent advances in fast, mobile, computing, artificial intelligence, and machine learning.
The undergraduate minor in Robotics and Autonomous Systems requires that students complete a total of 12 credit hours.
- Students must complete ECE/ME 5463 (Intro to Real Time Robotics Systems) and one elective course (minimum of 3 credit hours) from the following list of approved courses.
- In addition to section 1, the remaining 6 credit hours can be chosen from the following options:
- Any elective courses from the following list of approved courses.
- Undergraduate research credit (4998/4999/4999H) within AE, CSE, ECE, ISE, or ME.
- The research project must be relevant to the minor and is subject to approval of minor coordinator (Dr. Haijun Su).
- No more than 3-credit hours of coursework graded Satisfactory/Unsatisfactory may count towards the minor.
|Course #||Course Title||Credit Hours||Semester Offered|
|ECE/ME 5463||Introduction to Real Time Robotics Systems||3||Autumn and Spring|
Select a minimum of 3-credit hours from the following courses.
|Course #||Course Title||Credit Hours||Course Description|
|ME 5372||Design and Control of Mechatronics Systems||3||Introduction to multi-domain (mechanical, thermal, fluid, electrical, electronic, electro-mechanical) system design, dynamic modeling, and control system design and analysis techniques. Prereq: 3360 or 3361, or Grad standing in MechEng, or permission of instructor.|
|ME 5751||Design and Manufacturing of Compliant
Mechanisms and Robots
|3||Introduces methods and theories for kinematic and force analysis, synthesis of rigid body and compliant (flexible) mechanisms and robots. Pseudo-rigid-body model and CAD/CAE software will be used for modeling and analysis study. Students will be required to work on a team project to solve a real world design problem related to mechanisms and robots. Prereq: 3670 or equiv, or Grad standing in Engineering.|
|ME 5194*||Machine Learning for Engineers||3||The course will cover the foundations of various machine learning methods briefly and provide an applied hands-on introduction to machine learning as relevant to MAE and robotics. Applications in MAE and robotics will be explored in homework and project assignments, with subject-specific datasets and problems. *MECHENG 5194 is a temporary course number.|
|ME 5194*||Smart Product Design||3||Introduction to the concepts and process of embedded product design through an application based, structured design process and practice their application in the design of smart and interconnected products. *MECHENG 5194 is a temporary course number.|
|AE 5621||Guidance, Navigation and Control of Aerospace Vehicles||3||Spacecraft (satellite) control systems analysis and design. Prereq: 3521.|
|AE 5620||Stability and Control of Flight Vehicles||3||Analysis and design of aircraft, helicopter and missile flight control systems and the associated guidance and navigation systems. Prereq: 3521.|
|ECE 3551||Introduction to Feedback Control Systems||3||Provides fundamental concepts in feedback control systems design and analysis. Prereq: 3050.|
|ECE 5200||Introduction to Digital Signal Processing||3||Sampling and reconstruction; discrete-time rate conversion; processing of discrete-time signals; design of discrete-time filters, selected topics in adaptive and/or multidimensional signal processing. Prereq: 3050, and Stat 3470 or Math 4530; or Grad standing.|
|ECE 5553||Autonomy in Vehicles||3||Autonomy in the context of modern vehicles; cruise control, anti-lock brake systems (ABS), steering control/lane keeping; introduction to automated highway systems (AHS). Prereq: 3551, 5551, or 551, or Grad standing in Engineering.|
|ECE 5300||Introduction to Machine Learning||3||Coverage includes linear regression, linear classification, model and feature selection, neural networks, clustering, and principle components analysis. Python will be used for implementation examples. Prereq: CSE 1222 or Engr 1281.xx, and Math 2568 and Stat 3470, and enrollment in ECE major. Not open to students with credit for ECE 4194.02 (SP19, Machine Learning) or ME 5194 (AU19, Applied ML for MAE).|
|ISE 5520||Industrial Automation||1.5||Industrial Automation teaches the design, application, and computer logic and control of various mechanical, pneumatic, electrical, and electronic sensors and actuator devices for industrial systems. Prereq: 2500, or Grad standing in Engineering.|
|ISE 5525||Industrial Robotics||1.5||Operating principles, selection, use of proximity and optical sensors; switches, relays, actuators; electric motors and controls; electro-pneumatic devices; integration of these for automated industrial systems. Prereq: 2500, or Grad standing in Engineering.|
|ISE 5740||Cognitive Engineering Systems: Human-Centered Automation||3||Provides key concepts to make autonomous systems, robots, and artificially intelligent systems team players with responsible people. Prereq: Sr or Grad standing, or permission of instructor.|
|ISE 5760||Visual Analytics for Sensemaking||3||Students learn about information visualization techniques that help people analyze massive amounts of digital data to combat overload and aid sensemaking with applications in retail and financial decision making, logistics, information systems, manufacturing, healthcare, energy and smart grids, cybersecurity and social networks. Prereq: Jr, Sr, or Grad standing|
|CSE 5052||Survey of Artificial Intelligence for Non-Majors||3||Survey of the basic concepts and techniques in artificial intelligence, including problem solving, knowledge representation, and machine learning. Prereq: 1211, 1221, 1222, 1223, or 2221, or Grad standing. Not open to students enrolled in a CSE or CIS major.|
|CSE 3521||Survey of Artificial Intelligence 1||3||Survey of basic concepts and techniques in artificial intelligence, including problem solving, knowledge representation, and machine learning. Prereq: 2331 or 5331.|
|CSE 5524||Computer Vision for Human-Computer Interaction||3||Computer vision algorithms for use in human-computer interactive systems; image formation, image features, segmentation, shape analysis, object tracking, motion calculation, and applications. Prereq: 2331, or Sr or Grad standing.|
Key Topics Include:
- Robotic surgery and assistive device technology and their application to healthcare and rehabilitation
- Computer visions and image analysis for robotics
- Artificial intelligence and big data technologies for design, analysis and decision making in automated industrial systems and manufacturing robots
- Human interactions with robots and autonomous systems
- Practical applications of robotics and automation to macroscale/microscale manufacturing, energy and smart grids, cybersecurity and social networks
- Analysis and design of aircraft, helicopter, and missile flight control systems
- Spacecraft (satellite) control systems analysis and design