Design and Implementation of Multi-Degree of Freedom Robot Arm | ||||
Advanced Sciences and Technology Journal | ||||
Articles in Press, Accepted Manuscript, Available Online from 22 August 2025 | ||||
Document Type: Review Article | ||||
DOI: 10.21608/astj.2025.391676.1068 | ||||
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Authors | ||||
David Awad ![]() ![]() | ||||
1Mechatronics, Engineering and Technology, Egyptian Chinese University, Cairo, Egypt | ||||
2Mechatronics Engineering, Engineering and Technology, Egyptian Chinese University, Cairo, Egypt | ||||
3Departmant of Mechatronics Engineering, Engineering ,Egyptian Academy for Engineering and Advanced Technology, Cairo, Egypt | ||||
Abstract | ||||
A robotic arm is a programmable mechanical device designed to mimic the movement and functionality of a human arm. It consists of interconnected segments joined by joints, enabling precise and versatile motion, typically controlled by algorithms and software. In this paper, we present a multi-degree-of-freedom robotic arm designed for lightweight, low-cost applications, featuring a modular structure that allows for easy reconfiguration and scalability. The arm was developed using a combination of Multi-Body Simulation (MBS), Finite Element Analysis (FEA), and real-time control integration to optimize its mechanical performance. This work introduces a novel approach that combines geometric inverse kinematics solutions with real-time MATLAB-based control, ensuring high precision and responsiveness across diverse tasks. The robotic arm’s lightweight structure, manufactured using a mix of aluminum, and MDF components, balances structural integrity with cost-effectiveness, making it suitable for educational, research, and light industrial applications. Furthermore, the integrated MATLAB application provides a user-friendly interface for controlling the arm in real-time, with robust waypoint management and error detection capabilities. Our findings demonstrate that the proposed design offers a scalable and adaptable solution for a variety of pick-and-place operations, paving the way for future integration with vision systems and advanced machine learning algorithms to further enhance performance. | ||||
Keywords | ||||
Robot Arm; MATLAB; Multi-Body Simulation; Kinematics | ||||
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