Vision-Guided SCARA Robot for Sorting and Positioning Toys of Different Shapes for Arrangement

This project showcases a SCARA robotic system powered by deep learning algorithms, which uses visual guidance to recognize toys of different shapes and automatically sorts and places them in designated locations. The specific functions are as follows:

· Visual Recognition and Classification: The system utilizes deep learning algorithms to capture images of the workspace through a camera and identifies and classifies toys based on shape, color, and size. This process relies on a deep learning model trained to quickly and accurately detect and distinguish between various toys, achieving precise classification.

· Motion Control and Positioning: Once toys are classified, the SCARA robot uses visual information to calculate each toy’s position and orientation, controlling the robotic arm to place the toys in the designated area. This ensures that sorted toys are neatly arranged, achieving a tidy and aesthetic layout.

· Automation and Efficiency: By leveraging visual guidance and deep learning, the robot achieves efficient automated sorting and arrangement, greatly reducing manual intervention and improving operational efficiency.

This system demonstrates the application of deep learning algorithms in industrial automation. Through the integration of machine vision and robotic technology, the SCARA robot can adapt to various object shapes, performing high-precision classification and positioning tasks.