Robotics Engineering is an interdisciplinary field that involves electrical engineering, mechanical engineering, computer engineering as well as computer science, applied computing and artificial intelligence. It encompasses the research, development, design, build, and operation of different kinds of robots. They include, but not limited to, mobile robots, healthcare robots, industrial robots, military robots, agricultural robots, service robots, and space/underwater exploration robots. This program leads to a Bachelor of Science in Engineering - Robotics Engineering degree. This program prepares its graduates to enter the Robotics Engineering work environment with well-developed design and laboratory skills, to further study toward advanced degrees in Robotics Engineering, or to advance into managerial ranks and/or entrepreneurial endeavors in the Robotics industry. The Robotics Engineering program offers a rigorous curriculum that includes unique components that prepare students to succeed in their future careers. It helps students to build a solid foundation in Physical Sciences, Mathematics, and Engineering through both theoretical study and extensive hands-on laboratory learning experiences. It seamlessly integrates multi-disciplinary foundation courses from Electrical Engineering, Mechanical Engineering, Computer Engineering, and Computer Science into the Robotics Engineering curriculum. It incorporates the design, manipulation, programming, sensing, control and vision of robots through a sequence of core courses to cover every aspect of Robotics Engineering. It adopts an integrated design approach that begins with basic instruction of design and creativity during the first year and concludes with a capstone design project during the senior year. It also helps students to develop sensitivity to the social and humanistic implications of technology and motivate them to make worthwhile contributions to the profession and society, while upholding the highest standards of professional ethics. Furthermore, it prepares students for continuing study and professional development after they graduate. During the senior year, students are required to take the Fundamentals of Engineering (FE) examination.
Program Requirements
Required General Education
A course designed to improve students' understanding in communication, including the areas of interpersonal, nonverbal, listening, small group and public speaking.
Prerequisites:
none
Goal Areas:
GE-1B
Brief description of the operation of the US economic system illustrated by a discussion of current economic policies, issues, and problems. No credit toward a major, minor, or area with economics as a core, or if credit has been earned in ECON 201 and/or ECON 202, or equivalent.
Prerequisites:
none
Goal Areas:
GE-05
This introductory course covers digital systems topics including binary numbers, logic gates, Boolean algebra, circuit simplification using Karnaugh maps, flip-flops, counters, shift registers and arithmetic circuits. Problem solving methods, study skills and professional development will be addressed throughout the course.
Prerequisites:
MATH 112
The basic elements of electricity and electronics are explored in an internet enabled, self-paced course. Laboratories make use of a Virtual Laboratory environment to provide experience with issues in wiring, power, circuits, and digital electronics.
Prerequisites:
none
Goal Areas:
GE-03
Students in this course approach writing as a subject of study by investigating how writing works across a variety of contexts.
Prerequisites:
none
Goal Areas:
GE-1A
Limits, continuity, the derivative and applications, transcendental functions, L'Hopital's Rule, and development of the Riemann integral.
Prerequisites:
Satisfy Placement Table in this section, MATH 115 or both MATH 112 and MATH 113 with "C" (2.0) or better.
Goal Areas:
GE-04
Techniques of integration, applications of integration, improper integrals, numerical integration, the calculus of parametric curves, and infinite series and sequences.
Prerequisites:
MATH 121 with "C" (2.0) or better or consent
Goal Areas:
GE-04
Designed for science and engineering students. Calculus-based physics. Covers elementary mechanics including kinematics, statics, equilibrium and dynamics of particles, work and energy, rotational motion, gravitation, and oscillation. Lecture and Laboratory. MATH 121 must be completed with a C or better prior to taking this course or must be taken concurrently. High school physics or PHYS 101 is also strongly encouraged. Fall, Spring
Prerequisites:
none
Goal Areas:
GE-02, GE-03
Prerequisites to the Major
This course is a continuation of CIS 121. Students develop a basic knowledge of programming skills and object-oriented concepts, and use fundamental data structures such as lists, stacks, queues, and trees.
Prerequisites:
CIS 121. Select One Course: MATH 112, MATH 113, MATH 115, MATH 121, or MATH 130
To prepare students for engineering and technology education and profession through interactions with upper-class students, graduate students and practitioners from academia and industry; to prepare students for a career in electrical and computer engineering and technology.
Prerequisites:
none
his course presents algorithmic approaches to problem solving and computer program design using the C language. Students will explore Boolean expressions, implement programs using control structures, modular code and file input/output, and interface with external hardware using robots and sensors.
Prerequisites:
none
This course is meant to develop Electrical Engineering Circuit Analysis skills in DC and AC circuits. It includes circuit laws and theorems, mesh and node analysis. Natural and step response of RL, RC, and RLC circuits.
Prerequisites:
PHYS 222 or concurrent, MATH 321 or concurrent
Continuation of Circuit Analysis I to include special topics in circuit analysis.
Prerequisites:
EE 230 and EE 240, MATH 321, PHYS 222
Laboratory support for EE 230. Use of laboratory instrumentation to measure currents and voltages associated with DC and AC circuits. Statistical analysis of measurement data. Measurements of series, parallel and series-parallel DC and AC circuits. Measurement of properties for circuits using operational amplifiers. Measurement of transient responses for R-L and R-C circuits. Simulation of DC and AC circuits using PSPICE. Concepts covered in EE 230 will be verified in the laboratory. Pre-req: Must be taken concurrently with EE 230.
Prerequisites:
Must be taken concurrently with EE 230.
This course presents the theory, computations, and applications of first and second order differential equations and two-dimensional systems.
Prerequisites:
MATH 122 with "C" (2.0) or better or consent
Resultants of force systems, equilibrium, analysis of forces acting on structural and machine elements, friction, second moments, virtual work.
Prerequisites:
PHYS 221
Kinematics and kinetics of particles, systems of particles and rigid bodies, work-energy, linear and angular impulse momentum, vibrations.
Prerequisites:
ME 212
Designed for science and engineering students. Calculus-based physics. Covers electrical charge and field; magnetic field and its sources; current and resistance; simple DC and AC circuits; and electromagnetic induction. Lecture only. (Associated laboratory course is PHYS 232.) MATH 121 must be completed with a C or better prior to taking this course. MATH 122 must be completed before taking this course or taken concurrently. Fall, Spring
Prerequisites:
MATH 121 with a "C" or better; PHYS 221 with a "C" or better.
Major Common Core
This course covers robotic programming using the object-oriented programming language C++ where the program is embedded in the robot controller. Algorithms and design strategies that are specifically for robotic applications are introduced. The course also introduces the Robot Operating System (ROS) and the utilization of ROS for robotic programming and sensor data processing on mobile robotic electrical systems. In addition to the lecture, the course includes a lab that involves robotic hardware and software for the experiments of various robotic algorithms on real robots.
Prerequisites:
CIS 122
Varied topics in Electrical and Computer Engineering. May be repeated as topics change. Pre-req: to be determined by course topic
Prerequisites:
to be determined by course topic
A more advanced study of microprocessors and microcontrollers in embedded system design. Use of C language in programming, interrupt interfaces such as SPI, I2C, and CAN. External memory design and on-chip program memory protection are also studied.
Prerequisites:
none
Analysis of linear systems and signals in the time and frequency domain. Laplace and Fourier transforms. Z-transform and discrete Fourier transforms.
Prerequisites:
EE 230. MATH 321 and PHYS 222
Laboratory support for EE 334. Use of development boards and C programming language to handle I/O devices, interrupts, and all peripheral functions. Multiple functions such as timers, A/D converters, I/O devices, interrupts, and serial modules will be used together to perform desired operations.
Prerequisites:
Concurrent with EE 334
Signals and Systems, Fourier transforms, Parseval's theorem. Autocorrelation functions and spectral density functions. Information theory. Noise and noise figure, probability and statistics. Transformation of random variables, probability of error and bit error rate. Modulation and demodulation. Overview of analog, sampled analog and digital communication systems. Spread spectrum systems.
Prerequisites:
EE 341, MATH 223
Theory and principles of linear feedback control systems. Analysis of linear control systems using conventional techniques like block diagrams, Bode plots, Nyquist plots and root-locus plots. Introduction to cascade compensation: proportional, derivative and integral compensation. State space models.
Prerequisites:
EE 341
This course explains the interfacing method between a sensor and the microcontroller, describes the features and functions of several frequently used sensors, it then proceeds to explore the subject of sensor fusion, describe the algorithms how multiple sensors are used to extract correct and more useful information than each individual single sensor; finally the course also explores how a large number of sensor nodes are connected together via the wireless networking technologies to enable the monitoring and control of our environment to improve our life.
Prerequisites:
EE334 & EE344
This course covers the fundamentals of mobile robotic modeling, control, sensing and navigation planning. Frame coordinate systems and transformations are introduced along with physics driven dynamic differential continuous as well as discrete difference models. Algorithms associated with controller synthesis applied to path following based on sensor feedback are derived. The course also introduces electrical and mechanical implementation concepts in mobile robotic system design. In addition to the lecture, thecourse includes a laboratory component that involves the design and construction of robotic hardware and the development of associated software to test various robotic algorithms on real robots.
Prerequisites:
EE 358
Vision (whether in humans or robots) is fundamentally a computational process. Visual processes for machines must be able to deliver the kinds of capabilities that humans have: scene recognition, motion processing, navigation, and so forth. This course will begin by examining some of the elementary concepts in robot¿s vision. Subprocesses to be examined include edge detection, methods for obtaining shape information from images, object detection, space reconstruction and multi-view integration. The student will also be exposed to unsolved problems in these topics. The workload consists of programming and course projects
Prerequisites:
MATH 247, EE341
The design and organization of engineering projects. Project proposals, reporting, feasibility studies, and interpretation. Specification preparation, interpretation, and control. Issues involving creativity, project planning and control, and intellectual property rights. Students enrolled in this course must initiate and complete a design project in a small team format.
Prerequisites:
EE 332, EE 337, EE 341, EE 358. Select One Course: EE 333, EE 390. Select One Course: EE 334, EE 353. Select One Course: EE 350, EE 395
Completion of design projects and reports. Lectures on ethics, issues in contracting and liability, concurrent engineering, ergonomics and environmental issues, economics and manufacturability, reliability and product lifetimes. Lectures by faculty and practicing engineers.
Prerequisites:
EE 467 and Senior Standing
Machine Learning (ML) is the study of algorithms that learn from data, and it has become pervasive in technology and science. This course is an introductory course on the application of Artificial intelligence (AI) & ML in the field of Electrical and Computer Engineering. The course has three units. The first unit introduces several ML algorithms and Python programming languages. The second unit deals with autonomous driving. The last part deals with AI & ML-based wireless network design.
Prerequisites:
EE 341, EE 353
Surfaces, vector-valued functions, partial differentiation, multiple integration, and vector calculus.
Prerequisites:
MATH 122 with "C" (2.0) or better, or consent
Matrices, determinants, systems of linear equations, vector spaces, linear transformations, and characteristic value problems.
Prerequisites:
MATH 122 with "C" (2.0) or better or consent
This course offers a comprehensive introduction to the hardware aspects of robotics, tailored for undergraduate students with no prior experience in robotic systems. It blends theoretical foundations with practical applications, covering mechanical design principles, materials selection, actuators and sensors integration, electronics, control systems, and the integration of artificial intelligence into robotic hardware.
Prerequisites:
MATH 223, MATH 321, and Select 1 course: EE 341 or ME 341.
Major Restricted Electives
Choose 6 Credit(s).
The features, data rate, frequency range, and operation of several wireless networking protocols such as Wi-Fi, Low Energy Bluetooth, Near Field Communication, Radio frequency Identifier (RFID), Threads, and ZigBee that can be used to implement Internet of Things (IoT) are introduced. The electrical, functional, and procedural specifications of Wi-Fi are then examined in detail. The programming and data transfer using the hardware Wi-Fi kit are carried out to demonstrate the versatility of this protocol.
Prerequisites:
none
This course is a continuation of EE 358. Techniques for the analysis of continuous and discrete systems are developed. These techniques include pole placement, state estimation, and optimal control.
Prerequisites:
EE 358 and EE 368
Develop design and analysis techniques for discrete signals and systems via Z-transforms, Discrete Fourier Transforms, implementation of FIR and IIR filters. The various concepts will be introduced by the use of general and special purpose hardware and software for digital signal processing.
Prerequisites:
EE 341
Electrical power and magnetic circuit concepts, switch-mode converters, mechanical electromechanical energy conversion, DC motor drives, feedback controllers, AC machines and space vectors, permanent magnet AC machines and drives, induction motors and speed control of induction motors, stepper motors.
Prerequisites:
EE 230
The students will learn and practice their PLC programming knowledge in the Industrial Automation LAB. Learn programming and implementation of servo drive, VFD, Human Machine Interface (HMI) programming, Cognex vision system and controlling in a close loop with Allen Bradley ControlLogix PLC hardware.
Prerequisites:
none
This course introduces students the recent advances in real-time embedded systems design. Topics cover real-time scheduling approaches such as clock-driven scheduling and static and dynamic priority driven scheduling, resource handling, timing analysis, inter-task communication and synchronization, real-time operating systems (RTOS), hard and soft real-time systems, distributed real-time systems, concepts and software tools involved in the modeling, design, analysis and verification of real-time systems.
Prerequisites:
EE 107, EE 334, EE 395
The application of mechanics to the design and analysis of motion and force transmitting systems. Optimum design. Includes significant design component.
Prerequisites:
ME 417
Analysis of control systems using the methods of Evans, Nyquist and Bode. Improvement of system performance by feedback compensation. Introduction to digital control. Includes significant design component.
Prerequisites:
ME 341
Synergistic combination of mechanical engineering, electronics, controls and programming in the design of mechatronic systems. Sensors, actuators and microcontrollers. Survey of the contemporary use of embedded microcontrollers in mechanical systems, case studies. Includes significant design component.
Prerequisites:
ME 417, ME 463
General Electives
Choose at least 12 credits of General Education courses to meet Goal Areas 5, 6, 7, 8, 9, 10, as well as cultural diversity and writing intensive requirements. A recommended list of courses are AIS 211 (Goal Area 5, 7, Purple), EET 125 (Goal Area 6, 8, Purple), PHIL 224W (Goal Area 6, 9, writing intensive) and URBS 150 (Goal Area 10).
Policies
Admission to Major: Admission to the college is necessary before enrolling in 300- and 400-level courses. Minimum college requirements are:
A minimum of 32 earned semester credit hours.
A minimum cumulative GPA of 2.00 ("C").
Please contact the department for application procedures.
During the spring semester of the sophomore year, students should submit an application form for admission to the Robotics Engineering program. Admission to the program is selective and, following applications to the department, subject to approval from the department chair. The department makes a special effort to accommodate transfer students. Only students admitted to the program are permitted to enroll in upper-division courses. No transfer credits are allowed for upper-division engineering courses except by department chair review and approval.
Before being accepted into the program and admitted to 300-level engineering courses (typically in the fall semester), a student must complete the following courses including all necessary prerequisites:
General Physics I and II (calculus-based) (7 credits)
Calculus I, Calculus II and Differential Equations (12 credits)
Introduction to Electrical/Computer Engineering I and II (6 credits)
Circuit Analysis I and II (including lab) (7 credits)
English Composition (4 credits)
Data Structure (4 credits)
Statics and Dynamics for Electrical Engineers (3 credits)
A cumulative GPA of 2.5 for all science and math courses must have been achieved for program admittance. Grades must be 1.65 ("C-") or better for courses to be accepted.
GPA Policy: Students graduating with a degree in Robotics Engineering must have:
completed a minimum of 20 semester credit hours of upper division EE/ME course work;
have a cumulative GPA of 2.25 or higher in all upper division Minnesota State Mankato EE/ME coursework;
have completed their senior design sequence at Minnesota State Mankato; and
grades must be 1.65 ("C-") or better for courses taken at Minnesota State Mankato to be accepted
Petition to evaluate transfer credits must occur no later than the first semester the student is enrolled at Minnesota State Mankato.
All international students wishing to have transfer credits granted from non-U.S. schools will be required to use the ECE evaluation service to be completed no later than first semester at Minnesota State Mankato.
P/N Grading Policy: P/N credits can not be applied to any course that is used to meet the program requirements.
Degree Bachelor of Science in Engineering
Major Credits 80
Total Credits 120
Locations Mankato
Career Cluster Science, Technology, Engineering, Mathematics
