1. Overview
The DLAI-1221 artificial intelligence comprehensive training and assessment system is a training and assessment platform developed based on the above requirements. The platform consists of a high-performance computer, mobile terminal development module, data sampling and testing module, computer vision detection module, Harbot collaborative robot module, AMR robot based on two-dimensional code navigation, application scene simulation module, and other systems. The software platform is based on Windows (Linux Ubuntu 18.04 is optional) and modules such as Anaconda, Python, YOLOv5, OpenCV, and PyTorch are pre-installed.
DLAI-1221A artificial intelligence comprehensive training system simulates the intelligent picking process, Using the computer as the intelligent control center, together with high-definition cameras, collaborative robots, and AMR inspection robots, the cameras collect pictures of fruit crops and use AI algorithms to judge the ripeness and location information of the fruits, and then the collaborative robots pick them to complete smart picking.
2. System features
– Strong system integration: This platform integrates Python programming, YOLOv5 target recognition, OpenCV visual detection, AMR robot based on two-dimensional code navigation, collaborative robot system, and a variety of deep learning frameworks PyTorch and TensorFlow.
The equipment integrates artificial intelligence technologies such as computer vision and natural language processing; it is equipped with a simulation application simulation system, which can truly apply artificial intelligence algorithms, models, and applications to actual scenarios.
– 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 technology
– Object recognition using Python and OpenCV
– The production standards and process of artificial intelligence datasets
– Deployment and application of PyTorch-based deep learning framework
– Deployment and application of TensorFlow-based deep learning framework
– Application of computer vision based on YOLOv5
– Application of 2D/3D vision
– PLC programming technology
– Collaborative robot programming control
– Programming control of AMR robot based on QR code navigation