Department Welcome
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Intelligent Robotics Systems Engineering emphasizes the joint application of Artificial Intelligence, Robotics, Internet of Things and Smart Systems into engineering. Through those applications, students will learn methods and technologies in the fields of robotics and automation, including industries such as automotive and transportation, communication technologies, marine technology, and logistics, preparing them for careers in this exciting and rapidly growing field.
Introduction Video for Intelligent Robotics Systems Engineering
See what we have to offer in this exclusive welcome video.
Academic Members
List and details of academic members of the department.
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Study Plan
Details about the study plan and curriculum.
Course Curriculum: 160 Credit Hours
Guidance Plan
Guidelines and plan for student guidance.
Course Curriculum: 160 Credit Hours
List of Competencies
Intelligent Robotics Systems Engineering - List of Competencies
Specific intended learning outcomes grouped by knowledge and skills:
- Knowledge Intended Learning Outcomes:
- A1. Understanding the basic principles and theories of robotics, including mechanics, movement, control, sensing, and planning.
- A2. Understanding different types of robotic platforms and sensor technologies, as well as gaining the knowledge of the ethical and societal implications of robotics and AI. A3. Understanding the engineering concepts behind the design, implementation, testing, and analysis procedures in various robotic systems and algorithms.
- A4. Understanding the importance of knowledge integration from different disciplines with intelligent robotics systems engineering.
- A5. Encouraging lifelong learning on contemporary topics, fostering teamwork, and enhancing students' communication skills through team projects.
- Skills Intended Learning Outcomes:
- B1. Providing students with the skills of conducting experiments, analyzing and interpreting data to draw conclusions in intelligent robotics systems engineering fields.
- B2. Using primary and secondary sources of information to be capable of pursuing further studies and preparing lifelong learners.
- B3. Acquiring proficiency in programming languages and software commonly used in robotics.
- B4. Utilizing interdisciplinary knowledge to conduct research and solve complex problems in the field of robotics and AI.
- B5. Provide students with specific skills and critical thinking skills to find the right solutions for problems by using the most current methodologies and technology.
- Thinking Skills Intended Outcomes:
- C1. Developing critical thinking skills to solve problems in intelligent robotics systems engineering
- C2. Developing the skills of generating ideas and concepts to solve problems in intelligent robotics systems engineering.
- Other skills intended outcomes:
- D1. Developing the knowledge of the value of engineering ethics and the resolution of ethical dilemmas.
- D2. Developing the ability to work independently and collaboratively.
- D3. Developing presentation skills.
Course Description
Detailed descriptions of the courses offered.
| 101201 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0903101+0904101 | - | |
| Students will learn about the concept of static bodies under equal forces of contradictive direction. This course deals with the kinematics of particles; displacement, velocity, and acceleration relationships, equations of motion for constant acceleration; two-dimensional motion of particles, and projectiles; kinetics of particles, force-acceleration, work-energy, impulse-momentum; kinematics of planar rigid bodies, pure rotation, general motion; kinetics of planar rigid bodies, force-acceleration, work-energy, impulse-momentum; and an introduction to three-dimensional dynamics of rigid bodies; and an introduction to vibrations. | ||||
| 101211 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 904102 | - | |
| Circuit variables and elements, Kirchhoff's laws, simple resistive circuit analysis, voltage and current dividers, Delta to Wye and Pi to Tee equivalent circuits, circuit analysis techniques (mesh and nodal analysis), Thevenin?s and Norton?s equivalent circuits, basics of active circuit elements, transient analysis of RL, RC and RLC circuits. | ||||
| 101213 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101211 | - | |
| Sinusoidal steady-state analysis and power calculations and balanced three-phase circuits. It also covers the complex frequency and its use in circuit analysis, the frequency response, and two-port networks. Transformers: construction, principles, and operation, ideal and practical, performance characteristics, three-phase, autotransformers. DC machines: construction, classifications, performance equations of generators and motors, Synchronous machines: construction, generator, and motor operations. Three-phase induction motors: construction, operation, performance calculations, starting, and speed control. | ||||
| 101214 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 101213 | - | |
| DC circuit: Kirchhoff?s laws and mesh analysis, Thevenin?s and Norton?s theorems, superposition theorem, Wheatstone bridge. Transient response: RL, RC, and RLC circuits. AC circuits: impedance concept, frequency response, three-phase circuits. Y ? transformation. Maximum power transfer. Two-port networks. DC machines: construction, classifications, performance equations of generators and motors, Synchronous machines: construction, generator, and motor operations. Three-phase induction motors: construction, operation, performance calculations, starting, and speed control. | ||||
| 101215 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0401122+0401123 | - | |
| This course provides students with solid foundations in the basic concepts of programming data structures. The main objective of the course is to teach how to select and design computer structures that are appropriate for problems that might be encountered. Topics covered in this course include: linked lists, queues, stacks, trees, and other linked structures; also array list, heaps, hash tables, and graphs. The course is carried out within an object-oriented framework. Java programming language is used for implementation. | ||||
| 101221 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0401122+0401123 | - | |
| Introduction to programming basics (what it is and how it works), binary computation, problem solving methods, and algorithm development. Includes procedural and data abstractions, program design, debugging, testing, and documentation. Covers data types, control structures, functions, parameter passing, library functions, arrays, inheritance, and object-oriented design. Laboratory exercises in Python. | ||||
| 101240 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 903102 | - | |
| Numbering systems, basic gates, and logic functions, Boolean algebra, Boolean expressions, logic minimization techniques. Combinational logic building blocks: decoders, encoders, multiplexers, demultiplexers, and magnitude comparators. Digital arithmetic: adders and subtractors. Basics of sequential circuits: latches and flip-flops. Timing diagrams, counters and shift registers, basic PLDs, CPLDs, and FPGAs. State machines. System design with state machines using VHDL. Memory devices and systems: RAM ROM, FIFO, LIFO, and DRAM. | ||||
| 101310 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101350+101313 | - | |
| Transfer functions: block diagrams and signal flow graphs. Mathematical modeling of physical systems, state space representations, control systems characteristics, time response of systems and closed loop performance of second order systems, stability and Routh-Hurwitz stability criterion, root locus analysis, frequency domain analysis, design of control systems. Refrigeration cycles; vapor compression and absorption cycles, refrigeration system components, heat Pumps; heat recovery, gas cooling, and cogeneration systems, compressors, condensers, evaporators, expansion devices, refrigerants, and lubricants. | ||||
| 101311 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 0101310* | - | |
| analysis of first and second-order systems in open-loop and closed-loop configurations, stability of dynamical systems, system identification, design and tuning of different types of controllers, software packages for computer simulation, and design validation. | ||||
| 101312 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101213 | - | |
| Basic semiconductor concepts, diodes: DC and AC analysis, special type diodes, theory of Bipolar Junction Transistors (BJT): biasing techniques, BJT amplifier analysis, Field Effect Transistors (FET): biasing techniques, FET amplifier, simple applications of BJTs and FETs. | ||||
| 101313 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 0101214+0101312 | - | |
| Diode and diode applications including clipper, full-wave and half-wave rectifier, clamper, and voltage Doubler and Tripler. BJT transistor DC analysis for different configurations: Common base, common emitter, and common collector. BJT AC analysis. JFET DC analysis. Introduction to Op-amp. | ||||
| 101315 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101213 | - | |
| Transformers: construction, principles, and operation, ideal and practical, performance characteristics, three-phase, autotransformers. DC machines: construction, classifications, performance equations of generators and motors, Synchronous machines: construction, generator, and motor operations. Three-phase induction motors: construction, operation, performance calculations, starting, and speed control. | ||||
| 101315 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101215+903281 | - | |
| This course introduces the fundamentals concepts of Artificial Intelligence (AI), its evolution, and real-life applications. It covers the main aspects of AI, i.e., intelligent agents, problem formulation, and problem solving using uninformed and heuristic search algorithms. Moreover, students will be familiar with constraint satisfaction problems, adversarial search and games, expert systems, and genetic algorithms. The main concepts of machine learning, its tasks and respective algorithms are also introduced. Real world applications will be investigated through practical implementations using Python programming language. | ||||
| 101340 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101240 | - | |
| Basic architecture and assembly language of a microcontroller. Principles of microprocessor serial (asynchronous and synchronous) and parallel interfacing. Timers, A/D, and D/A relevant chips. Software and hardware interrupt handling routines. Application of top-down design to microcontroller software development in assembly language and a high-level language. Evaluation of hardware and software trade-offs. | ||||
| 101341 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101340 | - | |
| The Experiments in microcontrollers and embedded system lab focus on the design and implementation of several interfacing tasks; Interfacing with simple I/O devices like switches, LED, and analog sensors, and communicating with sensor modules with various communication protocols by using Arduino development boards. Also, it conducts experiments on bio potential signal acquisition and real-time signal processing, virtual system design, cloud programming, simulation, and debugging | ||||
| 101350 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0903102+0101213 | - | |
| Signal classifications and system properties: discrete and continuous time systems. Application of Fourier transformation to linear systems, Z-transform, system function, frequency response, and simulation in the frequency domain. | ||||
| 101351 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 101350 | - | |
| Students will learn and use Matlab to perform experiments in the field of signal and systems: Filtering, transmission through systems, Fourier analysis, convolution, and linear systems analysis. | ||||
| 101352 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0101312+0101340 | - | |
| Sensing and actuation in system instrumentation, Interfacing circuits, Application scenarios of sensors and actuators, Instrumentation process and steps, Application examples, Data acquisition and processing, Digital transducers, and Sensor technologies. | ||||
| 101353 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 101352 | - | |
| This lab introduces students to different types of sensors and actuators and some of their applications in addition to interfacing sensors devices and actuators with Arduino/ microcontroller circuits | ||||
| 101410 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101350 | - | |
| Transmission through a Linear System. Amplitude, Frequency and, Phase Modulation and Demodulation. Sampling Theorem, A/D, Conversion, Line Coding and M-ary. Baseband Transmission. Multiplexing Techniques: TDM, FDM. Digital Modulation and Demodulation Techniques: QAM, ASK, PSK and FSK | ||||
| 101415 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0101410+01012 21 | - | |
| An introductory course for Intelligent robotics. Introduction and an overview of manipulator types and their applications, robotic terminologies, transformation matrices, forward & inverse kinematic analysis, and kinematic decoupling. Forward & inverse dynamical analysis, Lagrange formulation, Newton-Euler Method. Path and motion planning based on spline interpolation. Jacobians and kinematic singularities, manipulators workspace determination. | ||||
| 101422 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0401122+0401123 | - | |
| This course provides an introduction to computer networks, with a special focus on Internet architecture and protocols. Topics include layered network architectures, addressing, naming, forwarding, routing, communication reliability, the client-server model, web and email protocols, and an A?Z overview of the Internet of Things. Besides the theoretical foundations, students acquire practical experience by programming. | ||||
| 101440 | 2 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 2 | 0 | 0101201+0102202 | - | |
| This course will focus on a solid foundation of design using computer aided design software. Students will work in 2-dimensional and 3-dimensional design. Including how to assemble 3-D models to show a complete design with multiple parts. Once designs have been completed students will produce detailed technical drawings used for the manufacturing of parts. Students will have the opportunity to use computer aided machining (CAM) to produce parts in the classroom. All other components needed will be sourced and provided based on student research and fundraising to produce their final robot design. This course will provide each student an opportunity to use modern software, tools, equipment, and practices to produce a uniquely designed robot. | ||||
| 101441 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 101440 | - | |
| This course includes experiments on topics covered by computer aided design. | ||||
| 101444 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101440+101221 | - | |
| This course is an important course offered in the 4th year and contains the following topics: Elements of Visual Perception, Image Sampling and Quantization, Image Processing and Analysis such as arithmetic and geometric operations, morphology, spatial and temporal operations, image transformations, and geometric operations, Image Formation: Camera Models, Calibration, Single and multiple view geometry, Feature extraction, triangulation, motion estimation, Visual Odometry Localization and Mapping: Initialization, Tracking, Mapping, direct and indirect geometric SLAM formulations Relocalization and map Optimization, Sensor combinations (IMU, mono vs. Stereo, RGB-Depth), Object detection, Instance recognition, Category recognition, Context, and Scene understanding. | ||||
| 101445 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 0 | 3 | 101444 | - | |
| The students utilize the available Robot platform using python programming and Matlab to control and command the motion of the Robot. In addition, the students will be able to visualize the robot's interaction with the controller and objects | ||||
| 101480 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| -- | Completion of 115Cr. Hr. | - | ||
| As part of their graduation requirements, undergraduate students should undergo training in a professional capacity at an engineering organization in Jordan or abroad. This experience consists of an eight-week internship in an engineering project with a professional organization that provides opportunities for training and exposure to real engineering practice. Typical venues for such experiences have to be approved by the department and include local, regional, and international engineering organizations. To demonstrate attaining their practical experience, students are required to submit at the end of their training a written report describing their experience. | ||||
| 101511 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | - | - | |
| An advanced course covering: An introduction to the design and implementation of intelligent mobile robot systems. This course will cover the fundamental elements of mobile robot systems from a computational standpoint. Issues such as software control architectures, sensor interpretation, map building, and navigation. | ||||
| 101527 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | Department Approval | - | |
| This course varies with the instructor?s course syllabus | ||||
| 101528 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | Department Approval | - | |
| This course varies with the instructor?s course syllabus. | ||||
| 101529 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101511 | - | |
| This course begins with the most important mechanisms that enable locomotion. The course then proceeds to mobile robot kinematics by applying principles of kinematics to the whole robot. The challenge of perception, mobile robot localization, and planning and navigation are also discussed. The course also covers intelligent agents, autonomous agents, autonomous robots, intelligent robots and the fine line between intelligent agents and autonomous robots. The course uses active learning techniques to guarantee better engagement from the students. Also, experts from the industry are invited to talk about the practical applications in this domain. This course includes assignments and a practical term project | ||||
| 101530 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 402331 | - | |
| This course introduces computer vision including fundamentals of image formation, camera imaging geometry, feature detection and matching, stereo, motion estimation and tracking, video processing, image classification and scene understanding. The course focuses on robotics applications and applications that include finding known models in images, depth recovery from stereo, camera calibration, image stabilization, automated alignment, tracking, boundary detection, and recognition. The course uses active learning techniques to guarantee better engagement from the students. Also, experts from the industry are invited to talk about the practical applications in this domain. This course includes assignments and a practical term | ||||
| 101545 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 0101311+0101415 | - | |
| An advanced course covering: Introduction to robotics, Participants in Fundamental of Industrial Robotics will come to understand the basic principles of robotics including the usage of servo motors for high-precision response and position, and optical encoders to detect a change in position and speed. They will learn about the axis and coordinate system used in programming to determine the robots target positions. | ||||
| 101558 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 101415 | - | |
| In-depth study of advanced automation concepts and robotic manipulators. Topics include 3-D kinematics, trajectory generation, compliance analysis, dynamic control of robotics along with concept of assembly operations and machine vision. Prerequisite: ME 421 or consent of instructor.? | ||||
| 101559 | 3 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| 3 | 0 | 402331 | - | |
| Neural networks have enjoyed several waves of popularity over the past half century. This course covers the history and the state-of-art of Neural networks and Deep learning approaches. The students will learn designing neural network architecture, Basic neuron models, Basic neural network models, and Basic learning algorithms. The students will develop applications by solving assignments in pattern recognition, image processing, and computer vision. Finally, the students will have opportunities to investigate open problems in this area. | ||||
| 101593 | 1 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| -- | Completion of 120Cr. Hr. | - | ||
| This is part one of a two-semester project. The project aims at tackling an applied mechanical engineering problem to strengthen the student?s capability and skills through a comprehensive and integrated approach. In this part, the student, along with his advisor, will develop the scope of work of the project, collect data, review the literature, and do any other work requested by his advisor. The student will submit a report to be evaluated by his advisor. | ||||
| 101594 | 2 CH. | Prerequisite | Co-requisite | |
|---|---|---|---|---|
| -- | 101593 | - | ||
| In this part of the project, the student will implement the scope of work developed in part one. The student will submit a comprehensive professional engineering report describing the project with results and conclusions. The student is required to give an oral presentation of the project to a committee that will evaluate both the report and the presentation. | ||||
Program Learning Outcomes
Intelligent Robotics Systems Engineering Program Learning Outcomes
Student learning outcomes describe what students are expected to know and be able to do by the time of graduation. By the time of graduation, the Intelligent Robotics Systems Engineering Department's program must enable students to attain an ability to:
- PLO1. An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
- PLO2. An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
- PLO3. An ability to communicate effectively with a range of audiences.
- PLO4. An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
- PLO5. An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
- PLO6. An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
- PLO7. An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.