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

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.