1. Overview
The hardware part of the DLAI-323 artificial intelligence fusion innovative application platform includes a collaborative robot, PLC, electric gripper, AGV, artificial intelligence workstation, intelligent integrated terminal, centralized dispensing mechanism, storage and buffer unit, retail scene model and human-computer interaction system partial composition, etc.
The artificial intelligence software platform adopts Anaconda + Python 3.8 to build the artificial intelligence environment and uses the mature PyTorch 1.7.1 framework to create basic algorithm modules, including DL_Annotation, CUDA, cuDNN, OpenCV, YOLOv5s and other artificial intelligence and image processing commonly used algorithm packages.
2. System features
– Strong system integration: DLAI-323 artificial intelligence fusion innovation application training workbench combines the integration innovation application of artificial intelligence technology in actual scenarios.
The AI teaching training equipment has a variety of control and computing platforms such as PC, Raspberry Pi, Jetson Nano, etc., combined with the application of core key technologies of artificial intelligence such as speech recognition, general object recognition, and face recognition, and is equipped with artificial intelligence technology applications such as centralized dispensing and smart retail Scenes.
It has a variety of robot application scenarios such as collaborative robot palletizing, curved surface trajectory, and drawing puzzles.
– Equipment safety: Equipped with corresponding leakage, overload and short circuit protection devices, which can effectively protect the safety of users.
3. Training object
– Python programming
– Data Acquisition of AI Datasets
– Data labeling of artificial intelligence datasets
– Data cleaning of artificial intelligence datasets
– Deployment and application of PyTorch-based deep learning framework
– Model training of artificial intelligence visual recognition model YOLOv5
– Application of computer vision based on PC and YOLOv5
– Application of computer vision based on Raspberry Pi and YOLOv5
– Application of computer vision based on Jetson Nano and YOLOv5
– Application of artificial intelligence offline face recognition unit
– Application of artificial intelligence speech recognition and synthesis unit
-Comprehensive application of artificial intelligence based on centralized dispensing application scenarios
-Comprehensive application of artificial intelligence based on smart retail application scenarios
-Deployment and application of TensorFlow-based deep learning framework
-Practical training on reading electrical drawings
-Pneumatic circuit takeover and electrical connection
-Application of detection switches, various sensors, and pneumatic components
-Installation and application of PLC, RFID, touch screen
-Robot communicates with PLC, touch screen communicates with PLC
-Collaborative robot plane drawing, curved surface work tasks
– Practical training of collaborative robot and visual communication
– Collaborative robot handling and palletizing tasks
– RFID reader communication application programming debugging