Detect, identify, and sort packages based on their color with Ned2
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This session takes place during a hands-on assignment where students are actively working on the robots. They were challenged to program the robot to complete a specific task, simulating a real-world industrial scenario. The activity will involve using the conveyor belt system in combination with an infrared (IR) sensor to detect and manage the movement of objects.
This practical exercise is designed to help students develop essential automation skills, including object detection, sensor integration, and motion control — all within a collaborative robotics environment.
The use the Ned2 robot with conveyor belt, IR sensor and vision system to stimulate a small production line that sorts different coloured package
Their goal is to program the robot to detect, identify, and sort packages based on their color — just like in a real industrial process.
The IR sensor is used to detect the presence of an object on the conveyor, triggering the camera system to analyze the package’s color. Once identified, the robot is instructed to pick up the package and place it in the correct location, simulating a color-based sorting workflow.
This type of practical task allows students to:
It’s a great example of how the Ned2 and the Discovery Bundle can bring Industry 4.0 concepts into the classroom through interactive, engaging learning experiences.
Newport & District Group Training Association (NDGTA) is an engineering apprenticeship training college based in Cwmbran, South Wales.
With a strong regional presence, NDGTA collaborates with 20 to 30 major companies operating across various sectors in and around South Wales. These partnerships allow the institution to stay closely aligned with industry needs and offer hands-on, career-ready training to its apprentices.
By combining technical education with real-world experience, NDGTA plays a key role in preparing the next generation of engineers, technicians, and industry professionals to meet the challenges of tomorrow’s manufacturing landscape.