I. Product description
Suitable for practical training projects such as"New Energy Vehicle Driving Assistance System Maintenance,""Assembly and Calibration of Environmental Perception Components,"and"Intelligent Sensor Technology,"Lidar structural understanding, assembly and calibration, and basic application development. The Lidar experiment box integrates comprehensive application training equipment for UDP protocol, TTL protocol, Lidar structural principles, assembly and calibration, and obstacle recognition. It requires a single-line Lidar, one piece of 13.3-inch industrial computer, a test vehicle, a wireless keyboard and mouse, and specialized tools to meet diverse development and learning needs. It also comes with instructional videos and relevant practical training accessories.
II. Technical requirements
1. Communication Protocol:
1) TTL (Transistor-Transistor Logic) serial port refers to a serial communication method that uses TTL-level signals for data transmission in electronic communications.
2) UDP is a simple network communication protocol, belonging to the transport layer protocol, used to transmit data within the network.
2. Input and Output Interfaces: The experiment box supports dual USB ports and a Gigabit Ethernet port, and can be expanded with COM ports, LPT ports, GPIO ports, etc.
3. Function 1: Combines FLASH technology to complete the disassembly and assembly of Lidar components, completing practical training on Lidar structure and principles;
4. Function 2: Combines Lidar assembly and testing software to complete practical training on Lidar detection;
5. Function 3: Combines Lidar calibration software to complete Lidar assembly calibration and performance testing;
6. Function 4: Combines Lidar development and application systems to complete comprehensive application training experiments on obstacle recognition.
III. Practical Training (Experimental) Projects:
1. LiDAR Structural Cognition Training;
2. LiDAR Performance Testing;
3. LiDAR Assembly and Calibration;
4. LiDAR Point Cloud Capture Application Development Experiment;
5. LiDAR Obstacle Recognition Application Development Experiment;
6. LiDAR Map Creation Application Development Experiment;
 
IV. Teaching Resources
1. Learning Worksheet: Includes lidar recognition, lidar quality testing, lidar debugging, lidar calibration, obstacle testing, and mapping experiments based on a ROS car.
2. Simulation Testing: Using intelligent driving simulation software, complete lane departure warning (LDW) and lane centering control (LCC).
 
V. Performance Parameters:
1. Appearance parameter:
1) Case Dimensions: Approximately 505*420*180mm
2) Operating Voltage: DC12V
3) Operating Temperature: -20°C - 60°C
2. Industrial Computer Parameters:
1) Processor: Intel Core i7
2) Memory: 4GB
3) Hard Drive: 128GB SSD
4) Operating System: Windows 10
3. Lidar Parameters:
Scanning Angle: 360°
Transmitting Repetition Rate: 4.5kHz
Angular Resolution: 0.8°
Scanning Frequency: 10Hz
Measurement Accuracy: ±3cm
Light Source: 905nm Laser
Measuring Range: 0-12m
Power Supply: 5V
Operating Temperature: -10°C - 40°C
Ingress Protection: IPX-4
4. Test Vehicle Parameters:
1) Product Dimensions: 269*194*65mm
2) CPU: ARM Cortex-A72 64-bit @ 1.5GHz (quad-core)
3) Computing power: 0.2TOPS (FP16)
4) Interfaces: 2 USB 2.0 ports, 2 USB 3.0 ports, Type-C network port
5) Minimum turning radius: 0.8m
6) Servo: S20F 20kg torque digital servo
7) Motor: MD36 35W brushed DC motor
8) Motor reduction ratio: 1:27
9) Maximum speed: 1.3m/s
10) Maximum gradeability: 17°
11) Obstacle crossing capability: 30mm

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