Master's thesis at the Northern Technical University researches (detection of change and analysis of urban growth with the participation of decision-making and integrated in CA Markov in geospatial assessment)
A master's thesis at the Technical College of Engineering - Kirkuk / Department of Electronic Engineering and Control, submitted by the student Hanan Hamid Ismail on 2/9/2024, discussed the development of a system for recognizing and holding objects based on the vision of the robotic arm and tagged "Development of a Vision-Based Object Recognition and Grasping System for a Robotic Hand"
The study dealt with: the application of the YOLOv8 algorithm to improve the performance of the robotic arm in industrial environments, where a large number of practical experiments were conducted on the robotic arm using the above algorithm. The study aimed to develop an integrated system based on the YOLOv8 algorithm to enhance the ability of the robotic arm to accurately identify, locate and catch objects in industrial environments, which contributes to increasing production and reducing errors.
Research results: The study revealed that after the application of the YOLOv8 algorithm, the ability of the robotic arm was enhanced and its accuracy and efficiency in recognition, locating and holding objects in real time increased. The results of this study can be used in industrial environments to increase production and reduce errors in complex industrial environments and precision manufacturing.
The discussion committee consisted of the honorable professors:
Prof. Abdulrahman Ikram Siddiq Chairman
Prof. Dr. Samir Saadoun Mustafa. Member
Assoc. Prof. Dr. Ali Najdat Nusrat. Member
Assoc. Prof. Dr. Montaser Idi Sharif. Member & Supervisor
Assoc. Prof. Farah Zuhair Jassim. Member & Supervisor
The discussion committee consisted of the honorable professors:
Prof. Abdulrahman Ikram Siddiq Chairman
Prof. Dr. Samir Saadoun Mustafa. Member
Assoc. Prof. Dr. Ali Najdat Nusrat. Member
Assoc. Prof. Dr. Montaser Idi Sharif. Member & Supervisor
Assoc. Prof. Farah Zuhair Jassim. Member & Supervisor

