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Commit 39e5800

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canchebagurjcarolinaresjhansson-ard
authored
[PC-1257] IMU Working Example Update (#1064)
* Accelerometer and gyroscope example section added * Content and grapichs update * Graphics updated, GIF added * Content update * Update content/hardware/06.nicla/boards/nicla-voice/tutorials/user-manual/content.md Good to me * Style fix Co-authored-by: Josefine Hansson <66409231+jhansson-ard@users.noreply.github.com> * Style fix Co-authored-by: Josefine Hansson <66409231+jhansson-ard@users.noreply.github.com> * Content update, Julian's review * Example code update * Content update, Julian's review * Number format update * Content update, Marta's review --------- Co-authored-by: Julián Caro Linares <j.carolinares@arduino.cc> Co-authored-by: Josefine Hansson <66409231+jhansson-ard@users.noreply.github.com>
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‎content/hardware/06.nicla/boards/nicla-voice/tutorials/user-manual/content.md‎

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@@ -50,7 +50,7 @@ Here is an overview of the board's architecture's main components shown in the i
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- **Microcontroller**: at the heart of the Nicla Voice is the nRF52832, a powerful and versatile System-on-Chip (SoC) from Nordic® Semiconductor. The nRF52832 is built around a 32-bit Arm® Cortex®-M4 processor running at 64 MHz.
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- **Speech and sensor-fusion processor**: the board features the NDP120 Neural Decision ProcessorTM, an ultra-low power always-on audio and sensor-fusion processor from Syntiant®, which enables several applications, including echo-cancellation, beamforming, noise suppression, speech enhancement, speaker identification, keyword spotting, acoustic event and scene classification, and multi-sensor fusion.
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- **Onboard advanced motion sensors**: the board features the BMI270, a high-precision IMU by Bosch® Sensortec, which combines a 3-axis accelerometer and a 3-axis gyroscope for precise motion tracking and orientation detection. The board also features the BMM150, a compact geomagnetic sensor from Bosch® Sensortec with a 3-axis magnetometer.
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- **Onboard advanced motion sensors**: the board features the BMI270, a high-precision Inertial Measurement Unit (IMU) from Bosch® Sensortec, which combines a 3-axis accelerometer and a 3-axis gyroscope for precise motion tracking and orientation detection. The board also features the BMM150, a compact geomagnetic sensor from Bosch® Sensortec with a 3-axis magnetometer.
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- **Onboard high-performance microphone**: the Nicla Voice is equipped with the IM69D130, a high-quality MEMS microphone by Infineon® Technologies. The IM69D130 offers excellent audio quality and low noise performance, ensuring accurate and distortion-free audio capturing.
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- **Onboard connector for external PDM microphone**: an external PDM microphone can be connected to the board via an onboard connector.
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- **Wireless connectivity**: the board supports Bluetooth® Low Energy connectivity, provided by the ANNA-B112 module developed by u-blox®. This compact, high-performance Bluetooth® Low Energy module allows the Nicla Voice to communicate wirelessly with other devices and systems.
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![Nicla Voice onboard magnetometer](assets/user-manual-12.png)
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The example code below demonstrates using the Nicla Voice board to perform Machine Learning inference on IMU (Inertial Measurement Unit) data. The code sets up event indicators using the onboard RGB LED and sends IMU data to the NDP processor for inference. The example can be found in the board's built-in examples by navigating to **File -> Examples -> NDP -> IMUDemo**.
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#### Accelerometer and Gyroscope Data
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The example code below shows how to get acceleration (m/s<sup>2</sup>) and angular velocity (in °/s) data from the onboard IMU and streams it to the Arduino IDE Serial Monitor.
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```arduino
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/**
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Nicla Voice accelerometer and gyroscope test sketch
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Name: nv_acc_gyro_test.ino
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Purpose: Sketch tests onboard accelerometer and gyroscope (BMI270)
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@author Arduino PRO Content Team
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@version 1.0 22/05/23
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*/
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#include "NDP.h"
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#include "BMI270_Init.h"
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// Named constants
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#define READ_START_ADDRESS 0x0C
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#define READ_BYTE_COUNT 16
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#define SENSOR_DATA_LENGTH 16
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// Accelerometer range is set to +/-2g
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// Raw accelerometer data is represented as a signed 16-bit integer
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// Raw accelerometer data can be converted to acceleration in m/s^2 units using the following scale factor:
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#define ACCEL_SCALE_FACTOR ((2.0 / 32767.0) * 9.8)
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// Gyroscope has a sensitivity of 16.4 LSB/dps
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#define GYRO_SCALE_FACTOR (1 / 16.4)
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/**
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Turns on and off the onboard blue LED.
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@param label to be printed on the Serial Monitor.
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*/
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void ledBlueOn(char* label) {
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nicla::leds.begin();
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nicla::leds.setColor(blue);
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delay(200);
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nicla::leds.setColor(off);
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Serial.println(label);
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nicla::leds.end();
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}
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/**
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Turns on and off the onboard green LED.
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*/
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void ledGreenOn() {
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nicla::leds.begin();
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nicla::leds.setColor(green);
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delay(200);
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nicla::leds.setColor(off);
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nicla::leds.end();
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}
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/**
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Blinks onboard red LED periodically every 200 ms.
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*/
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void ledRedBlink() {
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while (1) {
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nicla::leds.begin();
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nicla::leds.setColor(red);
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delay(200);
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nicla::leds.setColor(off);
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delay(200);
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nicla::leds.end();
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}
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}
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// Macros for checking the sensor status.
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#define CHECK_STATUS(s) do {if (s) {Serial.print("SPI access error in line "); Serial.println(__LINE__); for(;;);}} while (0)
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void setup() {
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int status;
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uint8_t __attribute__((aligned(4))) sensor_data[SENSOR_DATA_LENGTH];
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// Initiate Serial communication for debugging and monitoring.
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Serial.begin(115200);
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// Initialize Nicla Voice board's system functions.
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// Disable the LDO regulator on the Nicla Voice board for power saving.
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// Initialize the built-in RGB LED of the Nicla Voice board.
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nicla::begin();
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nicla::disableLDO();
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nicla::leds.begin();
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// Set up error and event handlers:
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// - In case of error, the red LED will blink.
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// - In case of match, the blue LED will turn on.
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// - In case of any event, the green LED will turn on.
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NDP.onError(ledRedBlink);
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NDP.onMatch(ledBlueOn);
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NDP.onEvent(ledGreenOn);
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// NDP processor initialization with firmwares and models
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Serial.println("- NDP processor initialization...");
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NDP.begin("mcu_fw_120_v91.synpkg");
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NDP.load("dsp_firmware_v91.synpkg");
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NDP.load("alexa_334_NDP120_B0_v11_v91.synpkg");
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Serial.println("- NDP processor initialization done!");
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// Set the BMI270 sensor in SPI mode, then read sensor data.
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status = NDP.sensorBMI270Read(0x0, 1, sensor_data);
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Read(0x0, 1, sensor_data);
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CHECK_STATUS(status);
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// Perform a software reset of the sensor.
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status = NDP.sensorBMI270Write(0x7E, 0xB6);
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CHECK_STATUS(status);
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delay(20);
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// Set the sensor back to SPI mode after the software reset.
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status = NDP.sensorBMI270Read(0x0, 1, sensor_data);
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Read(0x0, 1, sensor_data);
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CHECK_STATUS(status);
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// Disable power configurations.
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status = NDP.sensorBMI270Write(0x7C, 0x00);
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CHECK_STATUS(status);
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delay(20);
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// Prepare to load the sensor configuration.
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status = NDP.sensorBMI270Write(0x59, 0x00);
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CHECK_STATUS(status);
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// Sensor configuration.
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Serial.println("- BMI270 initialization starting...");
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status = NDP.sensorBMI270Write(0x5E, sizeof(bmi270_maximum_fifo_config_file), (uint8_t*)bmi270_maximum_fifo_config_file);
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CHECK_STATUS(status);
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Serial.println("- BMI270 Initialization done!");
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status = NDP.sensorBMI270Write(0x59, 0x01);
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CHECK_STATUS(status);
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delay(200);
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// Check sensor status.
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status = NDP.sensorBMI270Read(0x21, 1, sensor_data);
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CHECK_STATUS(status);
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// Configure the device to normal power mode with both accelerometer and gyroscope operational.
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// Set the accelerometer and gyroscope settings such as measurement range and data rate.
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status = NDP.sensorBMI270Write(0x7D, 0x0E); // Normal power mode
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Write(0x40, 0xA8); // Accelerometer configuration.
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Write(0x41, 0x00); // Set the accelerometer range to +/- 2g.
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Write(0x42, 0xA9); // Gyroscope configuration.
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CHECK_STATUS(status);
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status = NDP.sensorBMI270Write(0x43, 0x00); // Set the gyroscope range to +/- 2000 dps.
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CHECK_STATUS(status);
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}
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void loop() {
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// Allocate space for raw sensor data.
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uint8_t __attribute__((aligned(4))) sensor_data[SENSOR_DATA_LENGTH];
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// Declare variables for accelerometer and gyroscope data.
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int16_t x_acc_raw, y_acc_raw, z_acc_raw, x_gyr_raw, y_gyr_raw, z_gyr_raw;
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float x_acc, y_acc, z_acc, x_gyr, y_gyr, z_gyr;
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// Read operation status variable.
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int status;
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// Perform data read from the BMI270 sensor. The data read includes accelerometer and gyroscope data.
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// The sensor's read function is called with 0x0C as the start address and 16 as the number of bytes to read.
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// Collected data is placed into sensor_data array.
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status = NDP.sensorBMI270Read(READ_START_ADDRESS, READ_BYTE_COUNT, &sensor_data[0]);
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// Check the status of the read operation.
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CHECK_STATUS(status);
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// Parse the read sensor data. Data is in 16-bit format, where lower byte comes first (little endian).
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// Data for each axis (X, Y, Z) of the accelerometer and gyroscope is extracted from the array.
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x_acc_raw = (0x0000 | sensor_data[0] | sensor_data[1] << 8);
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y_acc_raw = (0x0000 | sensor_data[2] | sensor_data[3] << 8);
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z_acc_raw = (0x0000 | sensor_data[4] | sensor_data[5] << 8);
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x_gyr_raw = (0x0000 | sensor_data[6] | sensor_data[7] << 8);
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y_gyr_raw = (0x0000 | sensor_data[8] | sensor_data[9] << 8);
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z_gyr_raw = (0x0000 | sensor_data[10] | sensor_data[11] << 8);
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// Convert raw accelerometer data to acceleration expressed in m/s^2.
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x_acc = x_acc_raw * ACCEL_SCALE_FACTOR;
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y_acc = y_acc_raw * ACCEL_SCALE_FACTOR;
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z_acc = z_acc_raw * ACCEL_SCALE_FACTOR;
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// Convert raw gyroscope data to angular velocity expressed in °/s.
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x_gyr = x_gyr_raw * GYRO_SCALE_FACTOR;
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y_gyr = y_gyr_raw * GYRO_SCALE_FACTOR;
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z_gyr = z_gyr_raw * GYRO_SCALE_FACTOR;
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// Print accelerometer data (expressed in m/s^2).
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Serial.print("x_acc:");
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Serial.print(x_acc);
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Serial.print(",");
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Serial.print("y_acc:");
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Serial.print(y_acc);
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Serial.print(",");
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Serial.print("z_acc:");
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Serial.println(z_acc);
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// Print gyroscope data (expressed in °/s).
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Serial.print("x_gyr:");
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Serial.print(x_gyr);
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Serial.print(",");
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Serial.print("y_gyr:");
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Serial.print(y_gyr);
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Serial.print(",");
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Serial.print("z_gyr:");
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Serial.println(z_gyr);
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delay(1000);
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}
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```
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Here you can find a step-by-step explanation of the code:
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First, the necessary libraries are included:
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- `NDP.h` and `BMI270_Init.h` for the Nicla Voice board's basic functions and the IMU control.
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- Macros are defined for checking the status of the IMU; these macros allow the sketch to detect and handle sensor errors.
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Next, user functions `ledBlueOn()`, `ledGreenOn()`, and `ledRedBlink()` definition:
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- These functions allow the onboard LEDs to flash specific colors to indicate different states: blue for a successful match, green for an event, and red to indicate an error.
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Next, in the `setup()` function:
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- The serial communication is initialized at a baud rate of 115200.
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- The Nicla Voice board is initialized, and the LDO regulator (used for putting the board into power-saving modes) is disabled to avoid communication problems with the IMU.
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- Error and event handlers are initialized.
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- NDP processor is initialized; this process includes populating the external Flash memory of the board with the NDP processor internal microcontroller firmware (`mcu_fw_120_v91.synpkg`), the NDP processor internal DSP firmware (`dsp_firmware_v91.synpkg`), and the ML model (`ei_model.synpkg`).
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- The BMI270 sensor is initialized; this includes a software reset, loading the sensor configuration, and setting it into normal power mode with the accelerometer and gyroscope operational.
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Finally, in the `loop()` function:
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- Memory is allocated for the sensor data; data is then read from the sensor and stored in this allocated space.
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- Raw sensor data is then parsed and extracted into raw accelerometer and gyroscope data. This data is represented as 16-bit signed integers ranging from -32 768 to 32 767.
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- Raw sensor data is converted into understandable and standard unit measurements; for the accelerometer, data is converted to meters per second squared, and for the gyroscope, data is converted to degrees per second.
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- Converted accelerometer and gyroscope data are printed on the Serial Monitor, allowing the user to observe sensor data in real-time.
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After uploading the example code, you should see accelerometer and gyroscope data on the IDE's Serial Monitor as shown below:
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![Nicla Voice onboard IMU data on the IDE's Serial Monitor](assets/user-manual-13.png)
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Let's use also the Arduino IDE Serial Plotter to test the example IMU sketch; let's start visualizing only accelerometer data. To do so, comment the gyroscope data output as shown below:
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```arduino
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// Print accelerometer data (expressed in meters per second squared).
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Serial.print("x_acc:");
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Serial.print(x_acc);
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Serial.print(",");
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Serial.print("y_acc:");
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Serial.print(y_acc);
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Serial.print(",");
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Serial.print("z_acc:");
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Serial.println(z_acc);
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/* Print gyroscope data (expressed in degrees per second).
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Serial.print("x_gyr:");
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Serial.print(x_gyr);
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Serial.print(",");
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Serial.print("y_gyr:");
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Serial.print(y_gyr);
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Serial.print(",");
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Serial.print("z_gyr:");
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Serial.println(z_gyr); */
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```
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Upload the example sketch again and open the IDE's Serial Plotter by navigating to **Tools > Serial Plotter**. After a while, you should see a real-time graph showing data from the board's onboard accelerometer, as shown below (move the board):
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![Nicla Voice onboard accelerometer data on the IDE's Serial Plotter](assets/user-manual-14.gif)
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When the board is not moving, you should see acceleration measurements close to zero on the x and y-axis, while the z-axis will be close to 1g (approximately 9.81 m/s<sup>2</sup>). If you want to visualize gyroscope readings, uncomment the gyroscope data output and comment on the accelerometer data output; when the board is not moving, you should see gyroscope measurements on the three-axis close to zero.
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#### IMU and Machine Learning
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The example code below demonstrates how to use the Nicla Voice board to perform Machine Learning inference on IMU data. The code sets up event indicators using the onboard RGB LED and sends IMU data to the NDP processor for inference. The example can be found in the board's built-in examples by navigating to **File > Examples > NDP > IMUDemo**.
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```arduino
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#include "NDP.h"

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