CL-VC-001:  Intelligent Connected Miniature Vehicle

I. Product Introduction

This Intelligent Connected Miniature Vehicle is a model car specially designed for educational purposes. It utilizes precise Ackermann drive-by-wire chassis technology and is equipped with a 360-degree scanning LiDAR, high-precision inertial gyroscopes, and high-definition visual cameras to achieve accurate navigation and autonomous driving in complex indoor environments. The miniature vehicle can perform operations such as tracking, obstacle avoidance, detouring, and following traffic signs, fully simulating the behavior of real intelligent connected vehicles.

Thanks to its advanced AI computing platform, this miniature vehicle can perform image recognition, SLAM positioning, environmental perception, obstacle detection, and traffic sign recognition. The fusion of multi-sensor data as well as autonomous driving decision-making and control functions are also focal points of its teaching and research. Additionally, the miniature vehicle supports secondary development, providing researchers with great flexibility to customize vehicle functions according to specific teaching and research needs.

II. Overview of Main Functions

The Intelligent Connected Miniature Vehicle integrates the following core functions to provide a comprehensive teaching experience and research support:

1. Drive-By-Wire Chassis Design: Utilizing the Ackermann steering structure and equipped with CAN drive-by-wire protocols, the miniature vehicle not only simulates the physical form of intelligent connected cars but can also be used for in-depth understanding of the principles of automotive drive-by-wire chassis structures in teaching.

2. Autonomous Driving System Framework Learning: Its control system design is similar to the L4 level autonomous driving system architecture, allowing learners to gain a detailed understanding and practice of the four core technology modules of autonomous driving: perception, positioning, planning, and control.

3. Map Building and Navigation: It provides map-building tools to create detailed driving maps with traffic rule information, enabling the miniature vehicle to autonomously navigate to any specified target point based on map information.

4. Linkage with Simulation Software: The miniature vehicle can link with decision-making planning simulation bench software, synchronizing vehicle behavior with vehicle actions in the simulation software, deepening the understanding and research of autonomous driving behavior.

5. Vehicle-Road Cooperative Demonstration: By connecting to a cloud control platform, it can display real-time vehicle driving status information, support the demonstration of vehicle-road cooperative technology, and showcase the actual application scenarios of intelligent connectivity.

III. Detailed Specifications

The design details and technical specifications of the Intelligent Connected Miniature Vehicle are as follows:

1. Chassis Dimensions and Power Supply:

Model 1: Dimensions are Length 233mm, Width 191mm, Height 146mm; Model 2: Dimensions are Length 445mm, Width 358mm, Height 200mm. Both models provide 5V and 12V power supply interfaces to meet different energy needs.

Equipped with a front-wheel steering servo and rear-wheel drive mechanism, it supports precise control.

Equipped with a battery, control board, and remote controller to achieve remote control driving functionality.

1. Environmental Perception Components:

LiDAR: A single 16-line LiDAR with a measuring range of 0.15-12m, 360-degree scanning, a resolution of less than 0.5cm, an angular resolution of no more than 1 degree, a measuring frequency of 2000-8000Hz, and a scanning frequency of 1-10Hz.

IMU: A nine-axis sensor integrating accelerometers, gyroscopes, and magnetometers, with an onboard ATmega328 processor, outputs all sensor data through a serial stream, supporting multiple data output methods such as FTDI, Bluetooth, Xbee, with an input voltage range of 3.5-16V DC.

Camera: Maximum resolution of 1920*1080, supporting high-definition image capture.

Controller: Uses NVIDIA nano controller, based on the Ubuntu18.04 system, integrated with ROS Melodic, providing a powerful computing and control platform for autonomous driving research.

IV. Detailed Training and Learning Modules

The Intelligent Connected Miniature Vehicle is specially designed to enhance the teaching and practical training effects of autonomous driving technology, covering the following key learning modules:

1. ROS Environment Configuration: Provides an installation and basic configuration guide for the Robot Operating System (ROS), enabling learners to master the setup and basic operations of the ROS environment.

2. Sensor Application Training: Through practical teaching, gain an in-depth understanding of the working principles, data collection, and processing methods of various sensors (such as LiDAR, IMU, cameras, etc.).

3. Core Technology Learning of Autonomous Driving: (1) Positioning Technology: Introduces technologies for precise positioning using sensor data, such as GNSS, SLAM, etc. (2) Perception Technology: Discusses methods for identifying and understanding the vehicle's surrounding environment through environmental perception components. (3) Path Planning Technology: Teaches how to plan safe and efficient driving routes based on the vehicle's positioning and perception information

4. Control Technology: Involves how to precisely control the vehicle based on the planned route to achieve smooth driving.

1) Drive-By-Wire Chassis Principles and Protocol Learning: Delve into the working principles and related control protocols of the drive-by-wire chassis, helping learners to understand the foundational construction of modern intelligent cars

2) Map Recording and Production Techniques: Guide on how to use the miniature vehicle to record point cloud maps and create high-precision maps based on the recorded data, providing support for precise navigation in autonomous driving.