Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 17 | Machine Vision-Based Intelligent Fruit and Vegetable Picking & Sorting Robotic Arm |
Fengyi Jin Shengyu Xu Simeng Yan Wenye Zhang |
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| # Problem In agricultural production, the classification of produce (e.g., fruits and vegetables) based on dimensions or chromatic features is frequently required. Manual sorting is prone to error and incurs significant labor costs; conversely, a robotic arm specifically engineered for this task enables continuous 24-hour operation while substantially reducing operational expenses. # Solution Overview The robotic system leverages computer vision to recognize the size and color of workpieces, facilitating the real-time transfer of spatial coordinates and attribute data to the controller. The control architecture then drives the actuators to align the flexible end-effector with the target for autonomous grasping, followed by precise sorting into predefined areas based on the detected classifications. # Conponents ## Robotic Arm Composed of 4-6 motors and rigid arm. Able to move the end effector to specific position ## Gripper Penumatic Soft gripper with two fingers to grip objects without harm ## Machine Vision System Recognize object, category and send object position ## Control unit Get object position from vision system. Control robotic arm to certain position. Control gripper to grip. # Criteria of Success Be able to category according to color or size. Be able to grasp and put objects to certain areas according to their categories. |
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