BMI270 Example

This example shows how to use the espp::Bmi270 component to initialize and communicate with a BMI270 6-axis IMU.

Table of Contents

BMI270 Example

Features Demonstrated

Basic IMU Reading: Accelerometer, gyroscope, and temperature data
Orientation Filtering: Both Kalman and Madgwick filter implementations
Real-time Data Logging: CSV format output suitable for plotting
Interrupt Configuration: Data ready and motion detection interrupts
Advanced Configuration: Performance modes, bandwidth settings, power management

How to use example

Hardware Required

This example can run on any ESP32 development board with I2C pins available. Connect a BMI270 sensor as follows:

BMI270 Pin	ESP32 Pin	Description
VDD	3.3V	Power supply
VDDIO	3.3V	I/O power supply
GND	GND	Ground
SCL	GPIO22	I2C clock (configurable)
SDA	GPIO21	I2C data (configurable)
SDO	GND	I2C address select (0x68)
INT1	GPIO (optional)	Interrupt 1 output

Configuration

You can configure the I2C pins through menuconfig:

idf.py menuconfig

Navigate to: BMI270 Example Configuration

SCL GPIO Num: I2C clock pin (default: 22). If running on M5Stack Tab5, set to 32.
SDA GPIO Num: I2C data pin (default: 21). If running on M5Stack Tab5, set to 31.
I2C Clock Speed: I2C frequency in Hz (default: 1000000)

Build and Flash

Build the project and flash it to the board, then run monitor tool to view serial output:

idf.py -p PORT flash monitor

(Replace PORT with the name of the serial port to use.)

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example Output

The example outputs CSV-formatted data that includes:

Timestamp (seconds)
Raw accelerometer data (g)
Raw gyroscope data (°/s)
Temperature (°C)
Kalman filter orientation (radians)
Kalman filter gravity vector
Madgwick filter orientation (radians)
Madgwick filter gravity vector

Sample Output

I (298) main_task: Calling app_main()
[BMI270 Example/I][0.023]: Starting example!
[BMI270 Example/I][0.028]: Found BMI270 at address: 0x68
[Bmi270/I][0.036]: Setting power mode to 4
[Bmi270/I][0.039]: Loading BMI270 configuration file (8192 B), this may take some time...
[Bmi270/I][0.140]: Configuration file loaded successfully
[Bmi270/I][0.141]: BMI270 initialized successfully
% Time (s), Accel X (g), Accel Y (g), Accel Z (g), Gyro X (°/s), Gyro Y (°/s), Gyro Z (°/s), Temp (°C), Kalman Roll (rad), Kalman Pitch (rad), Kalman Yaw (rad), Kalman Gravity X, Kalman Gravity Y, Kalman Gravity Z, Madgwick Roll (rad), Madgwick Pitch (rad), Madgwick Yaw (rad), Madgwick Gravity X, Madgwick Gravity Y, Madgwick Gravity Z
[BMI270 Example/I][0.170]: Starting task...
186,-0.005,-0.052,0.993,0.000,0.000,0.000,27.3,-0.052,0.006,0.000,0.006,0.052,-0.999,0.000,-0.000,0.000,-0.000,-0.000,-1.000
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678,-0.006,-0.051,1.000,0.152,-0.183,-0.274,27.4,-0.051,0.006,0.000,0.006,0.051,-0.999,-0.051,0.006,-0.002,0.006,0.051,-0.999

Data Analysis

The CSV output can be imported into analysis tools like:

MATLAB/Octave: For advanced signal processing
Python (pandas/matplotlib): For data visualization
Excel/LibreOffice: For basic analysis
esp-cpp/uart-serial-plotter: For real-time plotting

Troubleshooting

Common Issues

No device found (Device ID read fails):

Check I2C wiring (SDA, SCL, power, ground)
Verify power supply voltage (3.3V)

Noisy data:

Check power supply stability
Add decoupling capacitors (100nF ceramic + 10µF electrolytic)
Ensure stable mechanical mounting
Consider using performance mode for gyroscope
Adjust filter bandwidth settings

No data updates:

Check if has_new_data() returns true
Verify ODR (Output Data Rate) settings
Check interrupt configuration if using interrupt mode
Ensure proper timing in update loop

Orientation drift:

Calibrate gyroscope offset
Tune filter parameters (process/measurement noise)
Consider magnetometer integration for yaw correction
Check for temperature effects

Debug Tips

Enable verbose logging:

config.log_level = espp::Logger::Verbosity::DEBUG;

Check register values:

uint8_t status = imu.read_u8_from_register(0x03, ec);  // STATUS register
fmt::print("Status: 0x{:02X}\n", status);

Monitor timing:

auto start = esp_timer_get_time();
imu.update(dt, ec);
auto elapsed = esp_timer_get_time() - start;
fmt::print("Update time: {} µs\n", elapsed);

Performance Notes

Update Rate: Up to 100Hz in this example (configurable)
Latency: < 1ms for basic IMU reading
Memory Usage: ~6KB stack for IMU task
CPU Usage: < 5% at 100Hz update rate on ESP32-S3
Power Consumption: ~685µA for BMI270 in normal mode

Advanced Features

The example can be extended to demonstrate:

Motion Detection: Any motion, no motion, significant motion
Step Counting: Pedometer functionality
Activity Recognition: Walk, run, still classification
Gesture Detection: Wrist gestures, tap detection
FIFO Usage: Batch data collection
Low Power Modes: Optimized for battery applications