Professional supplier of AI and robot teaching equipment
Professional supplier of AI and robot teaching equipment
The Collaborative Robot Vision Auto-Sorting Line is a desktop intelligent automation system designed for robot collaboration and vision-guided sorting. Combining collaborative robots, 2D and depth vision, conveyors, and warehouse modules, it provides complete training in object recognition, robotic picking, intelligent sorting, and warehouse automation. With locally deployed DeepSeek and Qwen models, the platform supports multimodal AI, autonomous task planning, and LLM-driven robotic applications.
(1) Data Types, Conversion, and Operations
(2) Basic Usage of Python Operators, Built-in Functions, and Sequences
(3) Program Selection Structures
(4) Experiment on Loop Structures
(5) List Experiment
(6) Set Experiment
(7) Function Applications
(8) String Experiment
(9) Data Processing in Python
(10) 0 File Operations in Python
(11) Extracting telephone numbers using regular expressions
(12) Data Visualisation
(13) Python Multi-Processing
(14) Multithreading in Python
(15) The Difference Between Python Processes and Threads
(16) Python-based Serial Communication
(17) Socket TCP Communication in Python
(18) UDP Socket Communication in Python
(19) Modbus Communication in Python
(20) Understanding Object-Oriented Programming in Python
(21) Using Python Classes and Class Instantiation
(22) Using Instantiated Objects in Python
(23) Using Inheritance in Python Classes
(24) Setting up the PyQt5 environment
(25) Using PyQt5
(1) Data Classification on the AdaBoost Movie Dataset
(2) Verification of a Two-Coin Toss Model using the EM algorithm
(3) Clustering of Unlabeled Data Using the K-Means Algorithm
(4) Film Genre Classification Based on the K-Nearest Neighbors Algorithm
(5) Dynamic Pedestrian Detection Based on HOG and Support Vector Machine (SVM)
(6) Decision Tree-Based Diagnosis of Breast Cancer
(7) Naive Bayes-Based Spam Filtering
(8) Face Recognition Based on Random Forests
(9) House Price Forecasting Based on Linear Regression
(1) Linear Regression Modeling and Training
(2) Clothing Classification Using a Neural Network
(3) Neural Network Regularization-Based Clothing Classification
(4) Optimization of Neural Network Parameters
(5) Building and Testing Neural Network Models
(6) Design of an Optimization Model Based on Residual Networks
(7) Neural Network Optimizer
(8) Handwritten Digit Recognition Based on LeNet
(9) Image Object Detection Based on YOLOv5
(1) Algebraic Operations on Images
(2) Image Processing, Encryption, and Decryption
(3) Spatial Domain Filtering
(4) Affine Transformations of Images
(5) Frequency-Domain Filtering of Images
(6) Morphological Rice Grain Detection
(7) Image Extraction Based on the Canny Algorithm
(8) Watershed-Based Contour Segmentation
(9) Hu Moment-Based Shape Matching
(10) Smoothing and Morphological Processing
(1) Introduction to the Vision System
(2) Pixel Dimension Measurement
(3) Bearing Dimension Measurement
(4) Object Localization and Angle Measurement
(5) Measurement of Object Edge Lengths and Area
(6) Object Color and Shape Recognition
(7) Offline Barcode Recognition
(8) Offline QR Code Recognition
(9) Character Segmentation
(10) Character Training and Recognition
(11) Product Surface Defect Detection Based on Morphological Processing
(12) LED Defect Detection
(13) Screw Appearance Defect Detection
(14) Camera Checkerboard Calibration
(15) Electronic Product Recognition
(16) License Plate Recognition Using OpenCV
(17) Vision-Based Barcode Recognition
(18) Vision-Based QR Code Recognition
(19) Vision-Based Object Shape and Color Recognition
(20) Vision-Based Fruit Classification
(1) Robotic Arm Fundamentals and Basic Operations
(2) Robotic Arm Teaching and Motion Control
(3) Calibration of the Robotic Arm and the Vision System
(4) Vision-Based Robotic Arm Object Classification
(5) Vision-Based Robotic Arm Object Palletising
(6) Vision-Based Robotic Arm Digital Sorting
(7) Vision-Based Robotic Arm Fruit Sorting
(1) Definition and Key Characteristics of Large Language Models
(2) Current Applications of Large Language Models Across Various Industries
(3) Data Collection and Preprocessing for Large Language Models
(4) Fine-Tuning and Training of Large Language Models
(5) Local Deployment and Inference of Large Language Models
(6) Local Service Integration and API Invocation of Large Language Models
(7) Prompt Engineering for Text-Based Large Language Models
(8) Intelligent Text Question-Answering Systems Based on Large Language Models
(9) Intelligent Voice Conversation Systems Based on Large Language Models
(10) Deployment and Applications of Multimodal Large Models
(1) Knowledge-Based Question Answering System Using Large Language Models
(2) Industrial Parts Sorting Experiment Based on Large Language Models
(3) Multimodal Large Model Applications Integrating Vision and Language
(4) Cloud-Based Large Model Image Generation Applications
Contact us if you need a custom course.
Answer:
The platform includes operation guides, experiment examples, teaching resources, source code, and videos. Teachers can start from basic robot operation and gradually extend to machine vision, AI algorithms, LLM applications, and robot automation projects.
Answer:
The Collaborative Robot Vision Platform is suitable for basic robot vision and LLM teaching. The Inspection Line includes two collaborative robots, two vision systems, a conveyor, a depth camera, and a storage module for inspection and collaborative automation. The Auto-Sorting Line focuses on visual recognition, bin picking, classification, and intelligent sorting applications.
Answer:
For a basic teaching budget, choose the Collaborative Robot Vision Platform. For smart manufacturing and inspection training, choose the Inspection Line. For AI sorting, logistics, and warehouse-related training, choose the Auto-Sorting Line.
Answer:
It supports Python programming, machine learning, deep learning, digital image processing, machine vision, robot control, vision-guided robotics, LLM technology, and multimodal AI applications.
Answer:
Yes. The computing unit supports local deployment of open-source LLMs such as DeepSeek and Qwen, enabling offline voice/text understanding, robot code generation, and LLM-based robot applications.
Answer:
Yes. The platform provides open software frameworks, SDKs, APIs, algorithm source code, and development manuals, allowing students to build custom AI, vision, robot control, and LLM applications.
Answer:
Optional modules include PLCs, depth cameras, additional sensors, AGVs, grippers, extra vision systems, larger AI computing units, LLM modules, and customized teaching scenarios.
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Yes. The system includes course resources, experiment guides, application cases, datasets, technical manuals, and development documents for classroom teaching and project-based learning.
Answer:
Yes. Different configurations can be provided according to teaching goals, budget, and project requirements. Please contact us for a customized recommendation and quotation.
Answer:
The product is delivered as a complete teaching system with hardware, software, accessories, and learning resources included. In most cases, you only need to prepare a power supply and classroom space.
Our engineers can help you choose the right platform, customize laboratory solutions, and provide technical support for your education and research projects.
✔ Product Selection
✔ Laboratory Planning
✔ Curriculum Support
✔ Global Technical Service
