Introduction
This training lab is designed for visual
perception in unmanned vehicle autonomous driving scenarios. It utilizes a
sandbox and an unmanned vehicle, integrating artificial intelligence algorithms
and LiDAR SLAM technology to achieve decision control, path planning, and
enable automatic driving of the unmanned vehicle within the sandbox
environment. The sandbox can simulate various common road conditions including
single lanes, double lanes, intersections, T-intersections, roundabouts,
crosswalks, as well as incorporate common traffic signs such as left turns,
right turns, parking areas, bus stops, and construction signs. The intelligent
unmanned car can autonomously identify the road environment and actively
perceive traffic signs to accomplish autonomous driving based on preset logic
within the sandbox. The training room covers the entire workflow from data
collection and annotation to model training/validation/reasoning/deployment
processes. This aims to foster "artificial intelligence +
transportation" integration.
Enterprise positions: data collection and annotation engineer,
artificial intelligence trainer, artificial intelligence application
development engineer, artificial intelligence system integration and operation
and maintenance engineer
Applicable majors: artificial intelligence engineering
technology/computer-related majors
Course products: professional core courses and professional extension courses in computer vision, deep learning
Project products: based on the driverless industry, multiple practical training projects focused on environmental perception, path planning, autonomous navigation, computer vision and other technologies
Intelligent hardware: smart car, teaching toolbox, simple sandbox,
customized sandbox
Applicable scenarios: professional teaching, comprehensive training, competition training
Feature
Derived from real industrial projects
- The project is based on Neusoft's characteristic industrial projects and is derived from real industrial projects and real business scenarios.
- Through project training, students learn project development in real business scenarios, avoiding the gap between simulated projects and real projects.
Combination of software and hardware with strong interactivity
The software and hardware are organically combined in the training process to achieve real feedback on the effect and increase the fun of the practice process.
Embodying the "Five New"
Closely follow the technological development of the unmanned driving industry and practical teaching methodology, and integrate new theories, new technologies, new tools, new products, new applications and other elements into projects and project supporting resources.