Object classifier conveyor system

Object Classifier Conveyor System

What is your project about?

The "Object Classifier Conveyor System" is an innovative automation solution designed for the efficient classification and sorting of objects using intelligent image recognition algorithm and robotics. The project is implemented as a ROS2 Humble Gazebo Classic simulation, where objects on a conveyor belt are identified by their Aruco markers and sorted onto different paths based on their classification. This system demonstrates the potential of AI in industrial automation, showcasing how it can enhance accuracy and efficiency in object sorting processes.

Why did you decide to make it?

The motivation behind this project stems from the increasing demand for automation in various industries, particularly in manufacturing and logistics. Traditional sorting systems are often limited in flexibility and accuracy, leading to inefficiencies and higher operational costs. By leveraging aruco recognition algorithm and robotics, this project aims to address these challenges, providing a more intelligent and adaptable solution for object classification and sorting. The decision to participate in the Hackerster AMD Pervasive AI Developer Contest further fueled the ambition to push the boundaries of what is possible with AI-driven automation.

How does it work?

The system consists of a conveyor belt that transports objects identified by their corresponding Aruco markers. There are three types of boxes in the simulation:

• Red Box (Aruco ID 1)
• Blue Box (Aruco ID 2)
• Green Box (Aruco ID 3)

Two cameras are strategically positioned above the conveyor belts:

• Camera 1: Placed above the left belt changer.
• Camera 2: Placed above the right belt changer.

As the conveyor belt moves, the cameras detect the Aruco markers on the boxes:

• When the red box (Aruco ID 1) reaches Camera 1, the left belt changer activates, diverting the box to the left belt.
• When the blue box (Aruco ID 2) reaches Camera 2, the right belt changer activates, diverting the box to the right belt.
• The green box (Aruco ID 3) continues straight on the main conveyor belt without diversion.

The system operates using ROS2 for seamless integration of sensors and actuators, and Gazebo for realistic simulation, providing a robust environment for testing and development.

What is the use case?

This project has significant implications for industries requiring precise and efficient object sorting. Potential use cases include:

• Manufacturing: Automated sorting of components based on type or destination, improving assembly line efficiency.
• Logistics and Warehousing: Streamlined sorting of packages based on destination, size, or content, enhancing order fulfillment speed.
• Recycling: Efficient categorization of recyclable materials, promoting better waste management and environmental sustainability.

By integrating aruco recognition algorithm with robotic automation, the "Object Classifier Conveyor System" exemplifies how technology can transform traditional industrial processes, making them smarter, faster, and more reliable. This project not only demonstrates technical prowess but also envisions a future where pervasive AI seamlessly integrates into everyday industrial operations.

Demo Video