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MicroROS V2 Robot Car📖
01.Introduction
  • 0.Unboxing Video
  • 1. Readme Learning Route
  • 2. Must Read Before Use
  • 3. Introduction to MicroROS V2 Control Board
  • 4. Introduction to LiDAR
  • 5. Introduction to ESP32 Camera Module
  • 6. FAQ
  • 7. About Charging
02.Assembly course
  • Assembly Video
03.Preparation
  • 1. Quickly Start
  • 2. Write Firmware
  • 3. Install VM and Start System
  • 4. Configure VM and Connect Robot
  • 5. Connect to MicroROS Agent
04.Quick start control course
  • 1. VM Keyboard Remote Control
  • 2. VM Handle Remote Control
  • 3. USB Handle Control
05.Robot control course
  • 1. Robot Information Release
  • 2. Robot Keyboard Control
  • 3. Robot Handle Control
  • 4. Robot State Estimation
  • 5. Linear Speed Calibration
  • 6. Angular Velocity Calibration
  • 7. Robot URDF Model
06.Lidar course
  • 1. Precautions for LiDAR Mapping and Navigation
  • 2. Lidar Avoid
  • 3. Lidar Following
  • 4. Lidar Guard
  • 5. Lidar Patrol
  • 6. Gmapping Mapping
  • 7. Cartographer Mapping
  • 8. Cartographer Quickly Repositioning Navigation
  • 9. Slam Toolx Mapping
  • 10. Navigation2 Single Point Navigation
  • 11. Navigation2 Multi Point Navigation
  • 12. Ros Robot App Mapping And Navigation
07.Road network planning
  • 1. Introduction to Road Network Planning and Quick Start
  • 2. Build a Pose Map
  • 3. Road Network Annotation
  • 4. Planning and Navigation Between Road Networks
  • 5. Road Network Navigation in Any Pose
  • 6. Path Replanning
08.Vision basic course
OpenCV Image Processing
  • 1. Introduction to OpenCV Source CV
  • 2. Open Source CV Geometric Transformation
  • 3. Open Source CV Image Processing and Drawing Text Line Segments
  • 4. Open Source CV Image Beautification
09.Visual General Course (For Standard&Superior version)
4. Yolov11&26 Visual Recognition
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Prediction
1. ESP32 Visual Recognition Module Configuration
  • 1. Serial Port Configuration WiFi Instructions
  • 2. Use ESP32 Camera Module in Robot Car
  • 3. Servo PTZ Calibration
2. OpenCV Visual Recognition
  • 1. Human Pose Estimation
  • 2. Object Detection
  • 3. AR Vision
  • 4. QR Code
  • 5. Color Recognition
  • 6. Facial Recognition
  • 7. AprilTag Machine Code Recognition
3. Mediapipe Visual Recognition
  • 1. Hand Detection
  • 2. Pose Detection
  • 3. Holistic Detection
  • 4. Facial Detection
  • 5. Facial Recognition
  • 6. Facial Special Effects
  • 7. 3D Object Recognition
  • 8. Brush
  • 9. Gesture Recognition
  • 10. Palm Target Localization
  • 11. Fingertip Trajectory Recognition
10.Visual Advanced Course (Just for Standard version)
1. Visual Control
  • 1. QR Code Recognition Control Action
  • 2. AprilTag Control Car Action Group
  • 3. Gesture Control Car Action Group
  • 4. Visual Line Tracking
2. Visual Tracking
  • 1. Color Tracking
  • 2. Facial Tracking
  • 3. QR Code Tracking
  • 4. Object Recognition And Tracking
  • 5. Mediapipe Palm Tracking
  • 6. Mediapipe Gesture Tracking
  • 7. Mediapipe Human Pose Tracking
  • 8. KCF Object Tracking
  • 9. AprilTag Machine Code Tracking
3. Visual Following
  • 1. Color Follow
  • 2. Face Follow
  • 3. QR Code Follow
  • 4. Mediapipe Palm Follow
  • 5. Mediapipe Gesture Follow
  • 6. Mediapipe Human Posture Follow
  • 7. AprilTag Machine Code Follow
  • 8. Object Follow
11.Visual Advanced Course (Just for Superior version)
1. Visual Control
  • 1. QR Code Recognition Control Action
  • 2. AprilTag Control Car Action Group
  • 3. Gesture Control Car Action Group
  • 4. Visual Line Tracking
2. Visual Tracking
  • 1. Color Tracking
  • 2. Facial Tracking
  • 3. QR Code Tracking
  • 4. YOLO Object Recognition and Tracking
  • 5. Mediapipe Palm Tracking
  • 6. Mediapipe Gesture Tracking
  • 7. Mediapipe Human Pose Tracking
  • 8. KCF Object Tracking
  • 9. AprilTag Machine Code Tracking
3. Visual Follow
  • 1. Color Follow
  • 2. Face Follow
  • 3. QR Code Follow
  • 4. Mediapipe Palm Follow
  • 5. Mediapipe Gesture Follow
  • 6. Mediapipe Human Pose Follow
  • 7. AprilTag Machine Code Follow
  • 8. Object Follow
12.AI Large Model Basic and Applications Course
1. AI Large Model Preparation
  • 1.AI Large Model Preparation
2. AI Large Model Basic Course
  • 1. AI Large Model Types and Principles
  • 2. RAG Retrieval Augmented and Training Samples
  • 3. Embodied Intelligent System Architecture
  • 4. Embodied Intelligence Core Source Code
3. AI Large Model Development
  • 1. Register Model Service Account
  • 2. Configure API KEY
  • 3. Dify Introduction
  • 4. Dify Basic Features
  • 5. RAG Knowledge Base Deployment
  • 6. AI Application Development Chatbot
  • 7. RAG Knowledge Base and Chatbot
  • 8. AI Agent Workflow
4. AI Large Model (Text Version)
  • 1. Semantic Understanding and Instruction Following
  • 2. Multimodal Visual Understanding
  • 3. Multimodal Visual Understanding + Basic Control
  • 4. Multimodal Visual Understanding + Object Following
  • 5. Multimodal Visual Understanding + Visual Line Following
  • 6. Multimodal Visual Understanding + SLAM Navigation
  • 7. Multimodal Visual Understanding + SLAM Navigation + Visual Line Following
  • 8. Multimodal Visual Understanding + SLAM Navigation + Object Following
  • 9. Intent Inference + Multimodal Visual Understanding + SLAM Navigation
13.Openclaw Basics Course
  • 1. Openclaw Introduction
  • 2. Openclaw Core Concepts
  • 3. Openclaw Api-Key Configuration
  • 4. Openclaw Switching Models
  • 5. Openclaw System Prompt
  • 6. Openclaw Common CLI Command
14. Openclaw Interaction Course
  • 1. Openclaw Webchat Interaction
  • 2. Openclaw Tui Interaction
  • 3. Openclaw Whatsapp Interaction
15.Openclaw Development Course
  • 1. Openclaw Robot Mcp Service Integration
  • 2. Robot CLI Command Tools
  • 3. Robot-Control Plugin Tools
  • 4. Openclaw Skills Development
  • 5. Openclaw Scheduled Tasks
  • 6. Openclaw Multi Agent System
  • 7. Openclaw Proactive Interaction
  • 8. Openclaw Vector Memory
16.Openclaw Embodied Intelligence Course
  • 1. OpenClaw Natural Interaction + Basic Control
  • 2. OpenClaw Natural Interaction + Slam Navigation
  • 3. OpenClaw Natural Interaction + Multimodal Visual Understand
  • 4. OpenClaw Natural Interaction + Multimodal Visual Understand + Slam Navigation + Visual Follow
  • 5. OpenClaw Natural Interaction + Multimodal Visual Understand + Slam Navigation + Visual Track
17.Multi-machine Course
  • 1. Multi Machine Handle Control
  • 2. Multi Machine Keyboard Control
  • 3. Multi Machine Navigation
18.MicroROS-V2 Control Board Development Environment
  • 1. Set Up the ESP32-IDF Development Environment
  • 2. ESP32-IDF Configuration Tool
  • 3. ESP Flash Tool Flashing Firmware
  • 4. Install ESP32 Microros Components
  • 5. Install And Start Microros Agent
19.MicroROS-V2 Control Board ESP32 Basic Course
  • 1. Led Light Up
  • 2. Button Function
  • 3. Drive Buzzer
  • 4. Oled
  • 5. Usb Host Function
  • 6. Serial Communication
  • 7. Battery Voltage Detection
  • 8. Drive Pwm Servo
  • 9. Drive Motors
  • 10. Read Motor Encoder Data
  • 11. Pid Motor Speed Control
  • 12. Robot Kinematics Analysis Theory
  • 13. Read Imu Data
  • 14. Read Lidar Data
  • 15. Flash Data Storage
  • 16. Custom Partition Table
  • 17. Bluetooth Communication
  • 18. Wifi Connection
  • 19. ESP32 Visual Recognition Module
20.MicroROS-V2 Control Board Micro_ros Basic Course
  • 1. Publish Topics
  • 2. Subscribe To Topics
  • 3. Multi Topic Subscription And Publishing
  • 4. Subscribe To Buzzer Topic
  • 5. Subscribe To Pwm Servo Topic
  • 6. Subscribe To Speed Control Topic
  • 7. Publish Odometry Topic
  • 8. Publish Imu Data Topic
  • 9. Publish Lidar Data Topic
21. Linux System Course
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
22.Docker Course
  • 1.Docker overview and docker installation
  • 2.Common commands for docker image containers
  • 3.Docker images deeply understand and publish images
23.ROS Basic Course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
Download
  • Mapping_APP(iOS_Android)
  • Code
  • Software_Tools
  • VM_System_File
  • 3D_Model_File
  • ESP32_Firmware
  • Dify LLM Base
  • Instruction_Manual
  • VMware
Download ZIP

Welcome to MicroROS V2 Robot Car repository

14. Read Lidar Data

Reading LiDAR Data

I. Experiment Objective

Learn how to receive the ranging data of the T-mini Plus LiDAR through the UART serial port on the ESP32-S3 platform. Master LiDAR data protocol parsing, ring buffer management, and multi-angle distance reading methods, laying the foundation for subsequent mapping, navigation, and obstacle avoidance functions.

II. Experiment Principle

1. Keywords

KeywordExplanation
LiDARA sensor that measures the distance to surrounding objects by emitting laser beams and measuring the time difference of the reflected light (TOF). The T-mini Plus is a 360° single-line LiDAR with a maximum ranging distance of 8m and a resolution of 1°, outputting multiple sets of distance data per second.
T-mini PlusA small, low-cost 360° LiDAR that uses the TOF ranging principle and outputs ranging data through a UART serial port (baud rate 230400). There are 360 sampling points per revolution, and the data includes angle, distance (mm), and signal strength.
UART serial communicationUniversal Asynchronous Receiver/Transmitter. This experiment uses UART1 (TX:GPIO17, RX:GPIO18) with a baud rate of 230400 in 8N1 mode. The LiDAR data is continuously transmitted to the ESP32 through the RX pin.
Ring bufferA fixed-size (1024 bytes) first-in-first-out circular queue used as a temporary cache for UART data reception. It solves the mismatch between the serial data reception rate and the CPU processing rate, avoiding data loss.
Protocol parsing state machineParses the LiDAR data packets byte by byte through a state machine: detect the packet header (0x55AA) → parse the packet type/length → receive the sampling data → checksum verification. After verification passes, update the 360° distance data.

2. Technical Architecture

The program adopts a three-layer architecture of serial reception + ring buffer + protocol parsing, with data passing layer by layer from the hardware to the application.

main/main.c
    └── Lidar_tminiplus_Get_Distance(angle)  /  Lidar_tminiplus_Get_Msg()
         └── components/lidar_tminiplus/         LiDAR driver encapsulation layer
              ├── lidar_tminiplus.c / .h        Data reception task + 360° data management
              └── tminiplus.c / .h              Protocol parsing layer (state machine + checksum)
                   └── components/uart1/        UART1 serial driver
                        ├── uart1.c / .h        Hardware initialization + transmit/receive interfaces
                        └── components/ring_buffer/  Ring buffer (1024 bytes)

Data flow: LiDAR UART output → ESP32 UART1 RX (GPIO18) → Uart1_Rx_Task reception task → ring buffer → Lidar_tminiplus_Task protocol parsing state machine → 360° scan data array.

III. Experiment Steps

1. Hardware Preparation

HardwareRequirement
MicroROS-V2 control board✅ Required
USB data cable (Type-C)✅ Required
T-mini Plus LiDAR✅ Required
Battery (12V)✅ Required (LiDAR power supply)

2. Prerequisites

  1. Set up the ESP32-IDF development environment

  2. Connect the MicroROS-V2 control board to the computer via USB

  3. Connect the T-mini Plus LiDAR correctly to the control board (UART interface)

  4. Turn on the chassis power to supply power to the LiDAR

3. Compile and Flash

​x

cd ~/esp/base_samples/read_lidar
source ~/esp/esp-idf/export.sh
idf.py build flash monitor

To exit the monitor: press Ctrl + ].

4. Stopping Method

In the terminal, press Ctrl+] to exit the serial monitor.

IV. Experiment Result

After flashing and running the program, you can see the following output in the serial monitor terminal:

xxxxxxxxxx
hello yahboom
I (1002) LIDAR_MAIN: Nice to meet you!
I (1012) UART1: Start Uart1_Rx_Task with core:0
I (1012) LIDAR_MAIN: distance:455, 523, 789, 1234
I (1212) LIDAR_MAIN: distance:452, 521, 785, 1230
I (1412) LIDAR_MAIN: distance:458, 525, 790, 1235
  • A set of distance values (in mm) for 4 angles is output every 200ms

  • The 4 values correspond to the 1°, 90°, 180°, and 270° directions

  • Cover the LiDAR with a hand or an object in different directions, and the distance value of the corresponding angle will change

  • The distance value changes with the actual distance of the obstacle; in an open environment it may show the maximum range value

V. Program Analysis

Source code paths:

  • Firmware source: ~/esp/base_samples/read_lidar/main/main.c

  • LiDAR driver: ~/esp/base_samples/read_lidar/components/lidar_tminiplus/lidar_tminiplus.h, lidar_tminiplus.c, tminiplus.h, tminiplus.c

  • UART driver: ~/esp/base_samples/read_lidar/components/uart1/uart1.h, uart1.c

1. Directory Structure

xxxxxxxxxx
read_lidar/
├── CMakeLists.txt
├── main/
│   ├── CMakeLists.txt
│   └── main.c
└── components/
    ├── lidar_tminiplus/        # T-mini Plus LiDAR driver encapsulation
    │   ├── lidar_tminiplus.h
    │   ├── lidar_tminiplus.c
    │   ├── tminiplus.h         # Protocol layer
    │   └── tminiplus.c
    ├── uart1/                  # UART1 serial driver
    │   ├── uart1.h
    │   └── uart1.c
    └── ring_buffer/            # Ring buffer
        ├── ring_buffer.h
        └── ring_buffer.c

2. Main Program Logic

main/main.c implements the LiDAR data collection function:

  1. Initialize the UART1 serial port

  2. Call tminiplus_GPIO_Init() to initialize the LiDAR driver and start the data reception task

  3. Send the start command {0xA5, 0x60} to wake up the LiDAR and start scanning

  4. Loop to read the distance values of 4 specific angles (1°, 90°, 180°, 270°) and print them

xxxxxxxxxx
static const uint8_t s_start_cmd[2] = {0xA5, 0x60};

Uart1_Init();
tminiplus_GPIO_Init();
Uart1_Send_Data((uint8_t *)s_start_cmd, sizeof(s_start_cmd));

while (1) {
    for (int i = 0; i < 4; i++) {
        distances[i] = Lidar_tminiplus_Get_Distance(points[i]);
    }
    ESP_LOGI(TAG, "distance:%d, %d, %d, %d",
             distances[0], distances[1], distances[2], distances[3]);
    vTaskDelay(pdMS_TO_TICKS(200));
}

3. Key Components

UART1 serial driver

Files: components/uart/uart1.h, components/uart/uart1.c

Pin configuration:

Parameter definition file: ~/esp/base_samples/read_lidar/components/uart1/uart1.h

SignalGPIODescription
TXDGPIO17UART transmit (connected to the LiDAR RX)
RXDGPIO18UART receive (connected to the LiDAR TX)

Communication parameters:

  • Baud rate: 230400

  • Data bits: 8 bits

  • Parity: None

  • Stop bits: 1 bit

  • Hardware flow control: Disabled

Working mechanism:

Uart1_Init() initializes the UART hardware and installs the driver, and also creates a reception task Uart1_Rx_Task that continuously reads data from the UART hardware and stores it in the ring buffer.

Core functions:

  • Uart1_Init() — Initializes the UART1 serial port with a baud rate of 230400 and creates the reception task (stack size 5KB, priority 5)

  • Uart1_Send_Data(uint8_t* data, uint16_t len) — Sends data

  • Uart1_Available() — Returns the number of readable bytes in the ring buffer

  • Uart1_Read() — Reads one byte from the ring buffer

Ring buffer

Files: components/ring_buffer/ring_buffer.h, components/ring_buffer/ring_buffer.c

Used as a temporary cache for UART data reception, implementing a first-in-first-out data buffering mechanism to avoid data loss.

Buffer size: 1024 bytes (RX1_BUF_SIZE).

T-mini Plus LiDAR protocol layer

Files: components/lidar_tminiplus/tminiplus.h, components/lidar_tminiplus/tminiplus.c

Data structures:

xxxxxxxxxx
#define TMINIPLUS_POINT_NUM  360U   // 360 sampling points per revolution

typedef struct __attribute__((packed)) {
    float angle;            // Angle (0°~360°)
    uint16_t distance;      // Distance (mm)
    uint8_t intensity;      // Signal strength
} tminiplus_ros_point_t;

typedef struct __attribute__((packed)) {
    uint16_t size;
    tminiplus_ros_point_t point[360];
} tminiplus_ros_data_t;

Data packet format:

A LiDAR data packet consists of a 10-byte fixed header and variable-length sampling data:

OffsetFieldSizeDescription
0PH (packet header)2 bytesFixed at 0x55AA
2CT (packet type)1 bytePacket type
3LSN (sample count)1 byteNumber of sampling points in this packet
4FSA (start angle)2 bytesAngle of the first sampling point
6LSA (end angle)2 bytesAngle of the last sampling point
8CS (checksum)2 bytesXOR checksum
10+Sampling dataLSN*3 bytes3 bytes per sampling point (intensity + distance)

Angle calculation formula:

xxxxxxxxxx
// Angle value = (register value >> 1) / 64.0
static float tminiplus_Level1_Start_End_Angle(uint16_t value) {
    return (float)(value >> 1) / 64.0f;
}

Distance decoding:

The raw distance value needs to be converted (shift right by 2 bits to remove the interference filtering flag):

xxxxxxxxxx
// Distance value = ((raw value >> 8) << 6) | ((raw value & 0x00FF) >> 2)
static uint16_t tminiplus_Si_To_Distance(uint16_t si_temp) {
    return (uint16_t)(((si_temp >> 8) << 6) | ((si_temp & 0x00FFU) >> 2));
}

Data reception state machine:

tminiplus_Data_Receive() uses a state machine to parse the serial data stream:

xxxxxxxxxx
RX_WAIT_AA -> RX_WAIT_55 -> RX_CT -> RX_LSN -> RX_FSA_L -> RX_FSA_H
  -> RX_LSA_L -> RX_LSA_H -> RX_CS_L -> RX_CS_H -> RX_DATA
  • After detecting the packet header 0xAA 0x55, parsing begins

  • Calculate the data length based on the LSN field, and receive the complete data packet after confirming it is within the buffer range

  • After reception is complete, perform checksum verification

  • If verification passes, update the LiDAR data and mark that a new data packet has arrived

Checksum algorithm:

xxxxxxxxxx
result = PH ^ (LSN<<8 | CT) ^ FSA ^ LSA;
for each point: result ^= intensity ^ distance;
// Verify that result == CS

LiDAR driver encapsulation layer

Files: components/lidar_tminiplus/lidar_tminiplus.h, components/lidar_tminiplus/lidar_tminiplus.c

Data reception task:

tminiplus_GPIO_Init() creates a dedicated task Lidar_tminiplus_Task during initialization (pinned to core 1, stack size 10KB, priority 10). This task continuously reads data from the UART and feeds it into the protocol state machine for parsing. When a complete new data packet is received, it calls Lidar_tminiplus_Update_Scan_Data() to update the 360° scan data.

ROS2 message structure initialization:

Lidar_Ros_Init() initializes the LaserScan message structure:

FieldValueDescription
angle_min-π rad (-180°)Scan start angle
angle_max+π rad (+180°)Scan end angle
angle_incrementπ/180 rad (1°)Angle increment
range_min0.12mMinimum ranging distance
range_max8.0mMaximum ranging distance

Data inversion (ENABLE_DATA_INVERSION):

Because the physical installation direction of the LiDAR may be inconsistent with the coordinate system definition of the robot, the tminiplus_remap_index() function remaps the angle index to ensure that 0° corresponds to directly in front of the robot. Specifically, the index is shifted by 180° and then modulo is applied.

Core functions:

  • tminiplus_GPIO_Init() — Initializes the LiDAR driver and starts the data reception task

  • Lidar_tminiplus_Get_Distance(uint16_t angle) — Gets the distance value at the specified angle (unit mm), angle range 0~359

  • Lidar_tminiplus_stop_Scan(uint8_t on) — Stops the LiDAR scanning (sends the stop command {0xA5, 0x65})

  • Lidar_tminiplus_Get_Msg() — Gets the complete LaserScan message (ROS2 message structure)

VI. Common Problems

ProblemCauseSolution
No LiDAR data outputThe LiDAR is not powered or the UART wiring is wrongCheck the battery power supply and confirm that GPIO17/18 are connected correctly
Distance value is always 0The LiDAR is not started or scanning is stoppedCheck whether the start command {0xA5, 0x60} was sent
Data does not updateThe serial reception task is blocked or protocol parsing failsCheck the baud rate configuration (should be 230400) and confirm the checksum algorithm is correct
No data at some anglesThe corresponding direction is out of range or the LiDAR is blockedConfirm that the LiDAR rotation has no obstacles and there is a target within 0.12~8.0m
Garbled dataSerial buffer overflowIncrease RX1_BUF_SIZE or raise the priority of the reception task
Read Imu Data
Flash Data Storage

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