Specific Object Picking Robotic Arm Using Haar Cascades

¹ Gokaraju Rangaraju Institute of Engineering and Technology, Department of Computer Science, Hyderabad, Telangana, India
² the Islamic University, Najaf, Iraq

Abstract

This project shows a robotic arm that can pick up objects. It was made with accuracy and speed in mind for use in factories. The robotic arm is very good at picking up metal nuts. It uses cutting edge technologies, like Haar cascade to find objects and inverse kinematics to figure out angles very accurately, to make its moves more exact and dexterous. A powerful computer vision method called Haar cascade is used to find metal nuts in the robotic arm's working environment. To do this, positive and negative pictures are used to train a Haar cascade classifier, which makes a model that can recognize the unique traits of metal nuts. The object recognition process makes sure that the nuts are located correctly, which lets the robotic arm deal with them in a controlled and precise way. The robotic arm uses inverse kinematics along with Haar cascading to figure out the exact joint angles needed for smooth, controlled movement. Inverse kinematics is very important for figuring out the joint setups that are needed to place the robotic arm's end-effector exactly on top of the metal nuts that have been found. Haar cascading for finding objects and inverse kinematics for accurate angle estimates work together to make sure that the robotic arm can pick up metal nuts in a variety of space arrangements. This combined system is a high-tech way to automatethe picking of specific items in manufacturing and assembly lines. It shows how industrial automation can be used to improve accuracy, efficiency, and flexibility.