Robust absolute 3D positioning in React Native, using sensor fusion to exploit the superior characterstics of the device Accelerometer, Gyroscope and Magnetometer, whilst mitigating against their negative qualities.
Physical data acquisition is implemented using react-native-sensors. The noise in sampled data is filtered from the input signals using the high quality kalmanjs, and sensor fusion is calculated using ahrs.
Using npm:
npm install --save react-native-sensor-fusionUsing yarn:
yarn add react-native-sensor-fusionimport React from 'react';
import { Text } from 'react-native';
import SensorFusionProvider, { useSensorFusion, useCompass, toDegrees } from 'react-native-sensor-fusion';
const Indicator = () => {
const { ahrs } = useSensorFusion();
const { x, y, z, w } = ahrs.toVector();
return (
<Text
children={toDegrees(z)}
/>
);
const Indicator = () => {
const { ahrs } = useSensorFusion();
const { heading, pitch, roll } = ahrs.getEulerAngles();
const compass = useCompass();
return (
<Text>
Heading: {toDegrees(heading)}°{'\n'}
Pitch: {toDegrees(pitch)}°{'\n'}
Roll: {toDegrees(roll)}°{'\n'}
Compass: {toDegrees(compass)}°{'\n'}
</Text>
);
};
export default () => (
<SensorFusionProvider>
<Indicator />
</SensorFusionProvider>
);| Prop | Type | Default | Required | Description |
|---|---|---|---|---|
| sampleInterval | number | 60 | No | The frequency to sample the device sensors in Hz. |
| algorithm | string | 'Mahony' | No | Choose from the Madgwick or Mahony filter. |
| beta | number | 0.4 | No | The filter noise value, smaller values have smoother estimates, but have higher latency. This only works for the Madgwick filter. |
| kp | number | 0.5 | No | The filter noise values for the Mahony filter (Proportional). |
| ki | number | 0 | No | The filter noise values for the Mahony filter (Integral). |
