MyRoboPath
Industrial Automation & AI
Est. 18 Hours
Budget: $180 - $270

AI Smart Vision Sorter with Jetson Nano & 4-DOF Gripper Arm

Build an automated industrial sorting cell: high-speed conveyor belt, real-time YOLO object classification, and robotic pick-and-place.

An industrial automation project combining edge AI and mechanical manipulation: camera inspection over a conveyor, real-time object classification and defect detection with YOLO, and a 4-DOF robotic arm sorting items into sorting bins.

Bill of Materials (BOM) & Components

ComponentSpecificationsQtyEstimated Cost
4-DOF Acrylic/Aluminum Robotic Arm Kit with GripperIncludes 4x MG996R metal-gear servos (10kg.cm torque)1$45
Mini DC Motor Conveyor Belt Assembly (30cm length)Adjustable speed DC motor with high-grip rubber belt1$38
NVIDIA Jetson Orin Nano or Raspberry Pi 5 + CameraReal-time vision classification pipeline1$85
Infrared Proximity Beam SensorDetects item arrival at inspection zone for hardware trigger1$5
5V 6A Regulated Power SupplyPowers all servos and sensors without voltage sag1$18

Electrical & Architecture Summary

IR beam sensor triggers Jetson camera capture. YOLOv8 identifies item class and coordinates. Inverse kinematics script commands the 4-DOF arm to grasp and deposit into the matching category bin.

Step-by-Step Assembly & Configuration

1

Conveyor & Arm Mechanical Integration

Duration: 4 Hours

Mount the sorting arm beside the conveyor drop-off zone. Position the top-down inspection camera perpendicularly over the conveyor.

Checklist:
  • Secure base plate to eliminate arm recoil during rapid movements.
  • Install lighting hood to provide constant illumination for the vision system.
2

Camera Calibration & Pixel-to-Millimeter Mapping

Duration: 4 Hours

Map camera pixel coordinates (u, v) to physical arm base Cartesian coordinates (X, Y) using a 2D affine perspective transformation.

Checklist:
  • Place reference markers on the conveyor belt surface.
  • Compute 3x3 perspective homography matrix using `cv2.getPerspectiveTransform`.
3

YOLOv8 Inference Pipeline & Pick-and-Place State Machine

Duration: 6 Hours

Deploy the classification model and write the master sorting state machine in Python.

Checklist:
  • Wait for IR beam trigger interrupt.
  • Capture frame, run YOLO inference, calculate grasping angle.
  • Execute IK trajectory: Lower Gripper -> Close -> Lift -> Move to Bin -> Release.