Published Paper Details:

This project focuses on the design, simulation, and intelligent control of a 6-axis robotic arm developed for automated pick-and-place operations integrated with object detection and artificial intelligence (AI) capabilities. The mechanical structure of the arm was precisely modelled using CATIA, allowing for detailed configuration of joints, links and degrees of freedom required for complex spatial movements. The robotic system was then simulated in MATLAB and Simulink, where kinematic models were constructed using Denavit-Hartenberg parameters for accurate forward and inverse kinematics. AI was integrated through the use of MATLAB's Machine Learning and Image Processing toolboxes, enabling the robotic arm to detect and classify objects using vision-based techniques. Object detection was enhanced using AI-driven image recognition algorithms, which allowed the system to identify object shape, colour and type with improved accuracy and adaptability. A PID control algorithm and trajectory planning ensured smooth, responsive motion for pick-and-place tasks. Additionally, the implementation of AI allowed the robot to learn from its environment and improve task efficiency over time, demonstrating adaptive decision-making capabilities. Simulation results confirmed the robotic arm's ability to autonomously detect, grasp and place objects in varying conditions with high reliability. This project illustrates the synergy of mechanical design, control systems and artificial intelligence in creating smart robotic solutions suited for modern industrial automation, warehousing, and smart manufacturing environments.