관성 센서 하드웨어 연결

관성 센서로 센서 융합 알고리즘 연결

아래의 예제에서는 Sensor Fusion and Tracking Toolbox™에서 제공하는 알고리즘을 사용하여 관성 센서를 설정하고 센서 데이터에 액세스하고 이러한 데이터를 처리하는 방법을 보여줍니다.

추천 예제

Estimate Orientation with a Complementary Filter and IMU Data

Stream IMU data from an Arduino and estimate orientation using a complementary filter.

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Estimating Orientation Using Inertial Sensor Fusion and MPU-9250

Obtain data from an InvenSense MPU-9250 IMU sensor, and to use the 6-axis and 9-axis fusion algorithms in the sensor data to compute orientation of the device.

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Wireless Data Streaming and Sensor Fusion Using BNO055

Get data from a Bosch BNO055 IMU sensor through an HC-05 Bluetooth® module, and to use the 9-axis AHRS fusion algorithm on the sensor data to compute orientation of the device. The example creates a figure which gets updated as you move the device.

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Binaural Audio Rendering Using Head Tracking

Track head orientation by fusing data received from an IMU, and then control the direction of arrival of a sound source by applying head-related transfer functions (HRTF).

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Estimate Phone Orientation Using Sensor Fusion

MATLAB Mobile™ reports sensor data from the accelerometer, gyroscope, and magnetometer on Apple or Android mobile devices. Raw data from each sensor or fused orientation data can be obtained. This example shows how to compare the fused orientation data from the phone with the orientation estimate from the ahrsfilter (Navigation Toolbox) object.

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Estimate Orientation Using AHRS Filter and IMU Data in Simulink

Stream IMU data from sensors connected to Arduino® board and estimate orientation using AHRS filter and IMU sensor.

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