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The BSc in Robotics and Artificial Intelligence (AI) is an interdisciplinary undergraduate program designed to equip students with the knowledge and skills required to design, develop, and implement robotic systems and AI technologies. 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 facilitate powering and driving the UAE鈥檚 knowledge-based economy.听 The degree consists of a comprehensive and diverse curriculum that provides the necessary knowledge, professional skills, and competencies needed for graduates in the field of robotics. BSc in Robotics and AI provides a comprehensive education that combines theoretical knowledge with practical skills, preparing graduates to be at the forefront of technological innovation with robotics and autonomous systems.
Students graduating with a BSc in Robotics and AI degree will attain the following:
The BSc in Robotics and AI program laboratories include:
These laboratories will be complemented by the following KU research laboratories:
The BSc in Robotics and AI students also have access to the laboratories in the other departments at KU.
ROBO Course Descriptions
ROBO 201 Motion Planning Algorithms for Robotics
Distribution: (3, 3, 4) Prerequisite: MATH112, 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 both mobile 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
This course offers a comprehensive introduction to robotics software development. Students learn how to employ widely adopted programming tools in robotics, including the Robotics Operating System (ROS), 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, including vector treatment of force systems and their resultants, static and equilibrium and dynamics, properties of areas, and distributed loads. Also, the course introduces rectilinear and curvilinear motion of particles, rotational and translational motion of rigid bodies, kinetics of particles and rigid bodies, and the principle of work and energy for particle and rigid body dynamics.
ROBO 204 Physical Embodiment of Robotic Systems
Distribution: (3, 3, 4)听 Prerequisite: PHYS 122
This course introduces the physical components of robotic systems, including sensors, actuators, controllers, electronic components, and system integration. It covers the design and selection of materials and machine elements. The course provides students with the hands-on skills necessary to build and optimize 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. The course also offers 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, build, and test robotic systems such as UAV, UGV, mobile manipulator, or manipulator to meet specified functional and non-functional requirements such as robustness and cost-effectiveness. 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. The course also covers software development, input/output programming including interrupts, analog to digital and digital to analog conversion.
ROBO 306 Robot Control
Distribution: (2, 3, 3) Prerequisite: ROBO302, ROBO303, MATH 211
This course introduces 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. Students study 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: COSC202, ROBO302, ROBO202
This course provides an in-depth exploration of various machine learning techniques applicable to robotics and autonomous systems. Students utilize sensor data from robotic devices to 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 covers robot vision for autonomous perception, navigation, and manipulation. Image acquisition, processing, feature extraction, stereo vision, pose estimation, and vision-based control techniques are also covered. This course includes classical and deep learning methods for object detection. Laboratorial experiments with real robots and with simulators are used to reinforce theory through practical implementation.
ROBO 402 Robotics and AI Engineering听
Distribution: (3, 3, 4) Prerequisite: ROBO304, ROBO305, ROBO308, MATH242
This course offers hands-on experience in developing embodied intelligence for AI-powered robotic systems. Students gain practical skills in synthesizing and integrating intelligent behaviors into robotic platforms. Key machine learning topics are revisited from an optimization perspective, with a consistent emphasis on their applications in robotics. The course also explores embedded AI as a powerful approach to addressing complex challenges in robotic systems.
ROBO 403 Robotic Manipulation and Grasping听
Distribution: (2, 3, 3) Prerequisite: ROBO306
This course covers theory and practice for autonomous robotic manipulation and grasping. This includes perception, grasp planning, kinematics, trajectory, and motion planning. It also includes tactile sensing, slip detection, and contact modeling during robot object interaction and force control. Different case studies, including bin picking, will be presented to support hands-on experimentation.
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 introduces the design, development, and application of autonomous robotic vehicles. Students learn to integrate mechanical, electrical, and software systems for perception, navigation, and control. Topics include sensors, motion planning, localization, and machine learning. Through theory and hands-on labs, students gain practical skills to build and program robotic vehicles for use in automotive, aerospace, underwater, and logistics industries.
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
ROBO 498 Senior Design Project II (3 Credits)
Prerequisite: ROBO 497
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.