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EDUCATION > Projects > KUKAtronics Robot

KUKAtronics Robot

Control and design for the KUKA robot trajectory tracking

Project Lead

WhatsApp Image 2021-08-14 at 9.15.43 AM.jpg

Assoc. Prof. Dr. Eng. Amir R. Ali 

Executive Deputy


Eng. Malek Mahmoud 

Project Members


Mohamed Hassan, B.Sc. (2018)


Mohamed Emad, B.Sc. (2016)


Salah Mahmoud, B.Sc. (2016)

Brief description for the project:

Industrial robot manipulators are multi-purpose machines used for industrial automation, which is one of the most crucial resources for development, in order to increase productivity, flexibility, and quality and help eliminate the human error in heavy and health-hazardous work by relying less on humans. Utilization of industrial manipulators in the field of automation has also proven to be very useful Robot motion control is a key expertise for robot manufacturers, and the current development focuses on improving the robot's performance, reducing its cost, insuring safety, and introducing new capabilities. Therefore, there is a continuous need to develop new models and control methods in order to fulfill all contradicting requirements, such as increased performance for a robot with lower weight. One main reason for this development of the robot mechanical structure is surely cost-reduction, but additional advantages are lower power consumption, improved agility, safety issues, and low environmental impact. This thesis is a project-based thesis discussing a trajectory motion control of a light-weight, educational purposed six-axis robotic arm. The KUKA robot presented in this thesis though being a relatively small educational one compared to the industrial robot manipulators mentioned above. It is greatly inspired in design by these manipulators including different design considerations like: the robot's weight issue and selection of suitable actuators (motors) required for driving it.


Challenges of the project:

The KUKAtronics is now designed and fabricated, it is controlled by kinematics, in the future we can controlled by different types of controllers, we can start implementing the EEG method which depends on the cross correlation method which is comparing brain frequencies and getting number of samples needed it is possible to implemented in the ARAtronics lab as we have all the know-how, materials needed so it will be applicable to start using the brain signal in the KUKAtronics control.

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