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This interdisciplinary undergraduate program equips students with the knowledge and skills required to design, develop, and implement robotic systems and AI technologies. It consists of a comprehensive and diverse curriculum that provides the necessary knowledge, professional skills, and competencies needed for graduates in the field of Robotics. The program also combines theoretical knowledge with practical skills, preparing graduates to be at the forefront of technological innovation with robotics and autonomous systems.
Through advanced skills in engineering, science, AI, robotics, and mathematics, students will aim to solve real-world problems and learn to use engineering tools to develop solutions that consider public health, safety, welfare, and global, cultural, social, environmental, and economic factors. Graduates will create prototypes using robotic and AI technologies, emphasizing sustainability, innovation, and entrepreneurship. They will gain the ability to model new robotic and AI applications, apply effective learning strategies, and communicate solutions and outcomes clearly both in writing and orally. The course also focuses on assessing ethical and professional responsibilities and making well-informed recommendations. Additionally, students will develop teamwork skills to foster a collaborative environment, set objectives, and formulate work plans in professional settings.
The program aims to prepare graduates for a wide range of careers and to supply the society with highly skilled, scientifically trained professionals in the field of Robotics and Artificial Intelligence, who can contribute to 鈥榩owering and driving鈥� the UAE鈥檚 knowledge-based economy. Graduates can pursue careers in various fields, including:
Students are also exposed to the latest advancements in technology that allow them to explore emerging professional trends such as:
The program involves acquiring knowledge in foundational courses in:
To acquire specialized knowledge with courses in:
Applicants for the BSc in Robotics and AI must satisfy Khalifa University鈥檚 general graduate admission requirements as well as program specific requirements. Click here to view the general requirements
Students who are short-listed for admission receive an invitation for admission interview. The invitation letter provides information about the scope of the interview and the areas that the interview committee will be assessing.
The program is delivered as a full-time program, with classes scheduled during the normal working day. There are no part-time, distance education, or web-based delivery modes. The minimum period of study will be four years from the date of first registration as a degree student. The maximum period of study is 6 years. Study is considered to commence from first enrollment in degree courses as a fully admitted (matriculated) student.
Most courses have a weighting of three or four credit hours. Normally, 1 credit hour of lecture represents 50 minutes of contact time per week over a 15- week semester. Typically, students are expected to dedicate 2 to 3 hours of independent study time for each hour of lectures. For laboratory courses, 1 credit hour represents 150 minutes of laboratory contact time per week.
Graduates will be able to:
Khalifa University has facilities and fully-equipped laboratories to support its Robotics and AI program.
The Robotics Teaching Labs, with state-of-the-art robotics platforms, dedicated for students includes:
Each of the Labs with approximately 100m2 in area will also have motion tracking systems. They are equipped with various robot hardware platforms (UGV, UAV, Marine Vehicles, Manipulators), robot sensors (cameras, Lidar etc), PCs, microcontrollers, and robot software.
These Labs are complemented by the following existing Khalifa University Center for Autonomous Robotic Systems (KUCARS) research labs including:
The BSc Robotics and AI students will also have access to the Labs in the Communication and IT, Computer Science, Mechanical Engineering and Electrical Engineering Departments at Khalifa University, including:
Khalifa University has state-of-the-art robotics research labs covering approximately 1000m2. These Labs have a variety of state-of-the-art robotics platforms that will be available for use by BSc in Robotics and AI students. KU dedicated Robotics Labs include the following:
Autonomous Car Lab – The lab is located at the University鈥檚 Sas Al Nakhl (SAN) campus., Figure 1. This facility has approximately 2 Kms of road network (illustrated in Figure 1), and has an autonomous EasyMile GEN 2 vehicle and two further Autonomous Vehicles. The project is being developed in collaboration with the Abu Dhabi Department of Municipality and Transport (DMT) for end user case studies and Etisalat by e& for providing the 5G telecommunications network. The autonomous vehicle operates in a rich mixed mode (other traffic and pedestrians) road network. Khalifa University also has two driving simulators and two further autonomous vehicle development platforms. It also has several other Unmanned Ground Vehicles (UGV) platforms including a Seekur UGV with a manipulator, a Husky UGV with a manipulator, Pioneer UGVs, and a Jackal UGV and a dedicated Computer Vision Lab engaged in autonomous driving research projects.
Figure 1 鈥� KU Autonomous Car Lab
Marine Robotics Lab – The Marine Robotics Pool, of dimensions 17mx10mx4.5m (illustrated in Figure 2), which includes wave and stream generating facilities equipped with an underwater tracking system. This robotics infrastructure is a world class facility including several unmanned underwater vehicles, including a Seabotix LBV under water ROV.
Figure 2 KU Marine Robotics Pool
Aerial Robotics Lab 鈥� Khalifa University has both outdoor and indoor labs for small UAV flight testing, with safety netting, as shown in Figure 3. The indoor Labs have two Optitrack Tracking Systems with 12 Prime cameras, VisualEyez II Motion tracking system and a Leica Absolute Indoor Tracking System (with absolute Interferometer, range 60m, and probing Range 20m with 0.001mm resolution). The Aerial Robotics Labs are equipped with a number of small UAV platforms (Steadidrone Vader, DJI Matrice , Astec Pelican , DJI 550, DJI 450), as well as larger UAVs including DJI Agras and fixed wing platforms.
Figure 3 KU Unmanned Aerial Vehicles Lab
The UGV Robotics Lab as seen in Figure, 4, is equipped with Seekur and Husky UGVs, several UAVs and sensing equipment including non-contact metal magnetic memory systems.
Figure 4 KU UGV Robotics Lab
The Grasping and Manipulation Lab and the Advanced Research and Innovation Center (ARIC) have a number of robot hands and manipulators including a KUKA manipulator (7DOF KR60-HA Robot, 60kg payload and equipped with a rail), a Mitsubishi manipulator (5DOF Robot Arm with 6kg payload), and a Baxter two arm Manipulator (2.2 KG Payload,7 DOF per arm). They are also equipped with a selective laser sintering machine, BigRep One 3D printer with a 1 cubic meter build area, and carbon fiber manufacturing and inspection capabilities.
Khalifa University鈥檚 computing teaching labs include file servers for high data accessibility throughout the campus. A Computing Lab with 24 multicore computers is equipped with state-of-the-art data analysis frameworks such as Anaconda, Big Data Technologies such as a Hadoop Cluster, NoSQL, extensive Python ecosystem, Fault tolerant fileservers (KU Drive), network + bandwidth, R Studio, Matlab, and other programming development platforms.
ROBO Course Descriptions
ROBO 201 Motion Planning Algorithms for Robotics
Distribution: (3, 3, 4) Prerequisite: MATH112, PHYS121, COSC114
This course provides knowledge on path planning algorithms for autonomous robot navigation within the context of the Robotics Operating System (ROS). Students explore examples relevant to mobile robots and manipulator robots. The course covers the representation of robot environment using configuration space, the construction of occupancy grid maps of obstacles, and the utilization of these maps for path planning.
ROBO 202 Software Development for Robotics
Distribution: (3, 3, 4) Prerequisite: COSC114
The course offers a comprehensive introduction to robotics software development. Students learn to program using widely utilized software packages in robotics. The course integrates hands-on laboratory sessions designed to complement theoretical classes, enabling students to apply techniques related to the physical embodiment of robots.
ROBO 203 Engineering Statics and Dynamics听
Distribution: (3, 3, 4) Prerequisite: PHYS122, MATH112
This course covers the fundamental principles of statics and dynamics of particles and rigid bodies. Kinematic equations for a particle, a system of particles, and rigid bodies are studied. Additionally, the course explores the principles of work and energy in particle and rigid body dynamics. Through projects, students apply these concepts.
ROBO 204 Physical Embodiment of Robotic Systems
Distribution: (3, 3, 4)听 Prerequisite: PHYS 122
This course addresses the physical components of robotic systems, including sensors, actuators, controllers, electronic elements, and system integration. It covers the design and selection of materials and machine elements. The course equips students with the practical skills necessary to create and refine physically embodied robotic systems.
ROBO 205 Electronic Circuits听
Distribution: (2, 3, 3) Prerequisite: MATH112, PHYS122
This course addresses the use of electrical and electronic circuits and components utilized in robotic systems. Students learn to analyze circuits and determine their steady-state and transient behavior. The course focuses on enabling robots to achieve autonomous behaviors by proper interfacing between sensors, actuators, and onboard computers. Also, it provides a thorough understanding of how electronic circuits underpin the functionality and autonomy of robotic systems.
ROBO 301 Signals and Systems听
Distribution: (2, 3, 3) Prerequisite: ROBO203, ROBO205
This course introduces analog and digital signal processing, essential to various engineering systems, including robotic perception and control. It covers the theory for analyzing continuous-time and discrete-time signals and systems. The course emphasizes applying signal processing principles in robotic applications, providing a solid foundation in the theoretical and practical aspects of signal processing in robotics.
ROBO 302 Robot Sensing
Distribution: (2, 3, 3) Prerequisite: ROBO204, ROBO205
This course examines how robots perceive their environment to execute navigation and manipulation tasks. Students evaluate the sensing requirements of real-world robotic applications and specify sensor characteristics to meet design specifications. Also, students learn to acquire, process, and interface sensor signals with robot platforms.
ROBO 303 Robot Modelling听
Distribution: (3, 3, 4) Prerequisite: ROBO203, ROBO204
This course covers the fundamental principles of kinematics and dynamics in robotic systems, with a focus on serial robotic manipulators and mobile robot platforms. It provides detailed case studies on various robotic systems, including robot manipulators, ground robots, and aerial robots. Through these case studies, students gain practical insights and the ability to apply theoretical concepts to real-world robotic applications, ensuring a robust understanding of robotic modeling.
ROBO 304 Design of Robotic Systems
Distribution: (3, 3, 4) Prerequisite:听 ROBO203, ROBO204, ROBO205
In this hands-on course, students learn to design, construct, and test robotic systems (e.g., UAV, UGV, mobile manipulator, or manipulator) to meet specified functional and non-functional requirements such as robustness and cost-effectiveness. Students collaborate in small teams under faculty supervision. The course covers the hardware and algorithms necessary for reliable and effective robot function.
ROBO 305 Embedded Systems听
Distribution: (2, 3, 3) Prerequisite: ROBO205, ROBO202
This course addresses the foundational role of embedded systems in robotics serving as a paradigmatic approach for embedded computing intelligence. Students gain hands-on experience in programming and understanding various micro-architectural components in modern robotics. Also, it covers software design in C, input/output programming including interrupts, analog to digital and digital to analog conversion.
ROBO 306 Robot Control
Distribution: (2, 3, 3) Prerequisite: ROBO302, ROBO303
This course offers an introduction to the dynamics and feedback control of linear time-invariant (LTI) systems. It provides fundamental design tools to specify stability, transient response, and steady-state response. Students acquire the skills to design Proportional-Integral-Derivative (PID) controllers to meet precise design specifications. Also, students apply these control strategies to achieve desired performance in robotic systems.
ROBO 307 Robot Localization听
Distribution: (3, 3, 4) Prerequisite: ROBO201, ROBO202
This course provides a comprehensive exploration of methodologies to resolve the localization challenges in autonomous robot navigation. The curriculum encompasses the study of common sensors, sensor models, and performance characteristics utilized in mobile robot pose estimation. Students develop expertise in integrating measurements for precise and robust pose estimation, as well as constructing high-definition 3D maps for state estimation of autonomous mobile robots.
ROBO 308 Machine Learning for Robotics
Distribution: (2, 3, 3) Prerequisite: ROBO302, ROBO202
This course provides an in-depth exploration of various machine learning techniques applicable to robotics and autonomous systems. The course integrates numerous projects, wherein students will utilize sensor data from robotic devices to practically implement machine learning algorithms in critical tasks of perception, navigation, and control, in the field of robotics.
ROBO 401 Robot Vision听
Distribution: (3, 3, 4) Prerequisite: ROBO302, ROBO301, ROBO308
This course addresses how robots employ computer vision to perceive their surroundings, thereby facilitating navigation and manipulation tasks. Students learn methods to acquire, process, and analyze visual data from robotic imaging systems. Practical projects and exercises will reinforce theoretical knowledge, ensuring a comprehensive educational experience.
ROBO 402 Robotics and AI Engineering听
Distribution: (3, 3, 4) Prerequisite: ROBO304, ROBO305
This course provides hands-on experience in developing embodied intelligence in AI robotics. Students acquire practical skills in synthesizing and integrating intelligent behaviors into robotic systems. The blend of theoretical knowledge and practical application supports the design and evaluation of AI-driven robots, preparing students for innovative challenges in robotics and artificial intelligence.
ROBO 403 Robotic Manipulation and Grasping听
Distribution: (2, 3, 3) Prerequisite: ROBO306
This course provides an in-depth exploration of algorithmic methods for autonomous robot grasping and manipulation in unstructured environments. Students explore model-based and learning-based approaches, covering robot perception, planning, dynamics, and control. Practical projects on bin picking and manufacturing assembly enhance theoretical knowledge, equipping students with skills to apply advanced techniques in real-world scenarios.
ROBO 404 Robots for Manufacturing听
Distribution: (2, 3, 3) Prerequisite: ROBO306
This course explores industrial robots’ impact on manufacturing and the fourth industrial revolution. Students learn about robot operation, history, societal impact, and trends, covering hardware, software, perception, planning, control, and human-robot interfaces. The curriculum includes collaborative robots and emphasizes the practical application of theoretical knowledge in factory automation.
ROBO 450 Robot Vehicles (2 Lecture, 3 Laboratory 鈥� 3 Credits)
Distribution: (2, 3, 3) Prerequisite: ROBO306, ROBO307
This course covers the key components and functions of autonomous vehicles, including cars, drones, and marine robots. Students learn software and hardware systems, advanced techniques for control, scene understanding, path planning, reasoning, and localization. Through theory and practical application in simulations and experiments, students gain a solid understanding of autonomous vehicle technology principles.
ROBO 451 Human Robot Interaction听
Distribution: (2, 3, 3) Prerequisite: ROBO401
This course covers fundamental concepts and theories of Human-Robot Interaction (HRI). Students explore methods and techniques for designing and evaluating robotic systems that interact seamlessly with humans. Combining theory and practical applications, the course equips learners with skills for innovative HRI solutions, including user-centered design, cognitive and social interaction, ethics, and real-world case studies.
ROBO 497 Senior Design Project I (3 Credits)
Prerequisite: 听听 ROBO302
This course involves team projects to design and develop robotic systems under specific goals and constraints. Teams apply theoretical and experimental methods, practicing critical thinking and evaluation. Guided through hypothesis generation, study, literature review, analysis, design, implementation, testing, and conclusion, students demonstrate initiative, engineering judgment, self-reliance, and creativity in an industry-like team setting.
ROBO 498 Senior Design Project II (3 Credits)
Prerequisite:听 Senior standing and department approval
This course involves team projects to design and develop robotic systems under specific goals and constraints. Teams apply theoretical and experimental methods, practicing critical thinking and evaluation. Guided through hypothesis generation, study, literature review, analysis, design, implementation, testing, and conclusion, students demonstrate initiative, engineering judgment, self-reliance, and creativity in an industry-like team setting.