android-Motion Sensors

> The Android platform provides several sensors that let you monitor the motion of a device. Two of these sensors are always hardware-based (the accelerometer and gyroscope), and three of these sensors can be either hardware-based or software-based (the gravity, linear acceleration, and rotation vector sensors).

> The Android Open Source Project (AOSP) provides three software-based motion sensors: a gravity sensor, a linear acceleration sensor, and a rotation vector sensor. These sensors were updated in Android 4.0 and now use a device's gyroscope (in addition to other sensors) to improve stability and performance. an instance of the default acceleration sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
  ...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_ACCELEROMETER);
Conversely, a low-pass filter can be used to isolate the force of gravity. The following example shows how you can do this:
public void onSensorChanged(SensorEvent event){
  // In this example, alpha is calculated as t / (t + dT),
  // where t is the low-pass filter's time-constant and
  // dT is the event delivery rate.

  final float alpha = 0.8;

  // Isolate the force of gravity with the low-pass filter.
  gravity[0] = alpha * gravity[0] + (1 - alpha) * event.values[0];
  gravity[1] = alpha * gravity[1] + (1 - alpha) * event.values[1];
  gravity[2] = alpha * gravity[2] + (1 - alpha) * event.values[2];

  // Remove the gravity contribution with the high-pass filter.
  linear_acceleration[0] = event.values[0] - gravity[0];
  linear_acceleration[1] = event.values[1] - gravity[1];
  linear_acceleration[2] = event.values[2] - gravity[2];
}

Using the Gravity Sensor


The gravity sensor provides a three dimensional vector indicating the direction and magnitude of gravity. The following code shows you how to get an instance of the default gravity sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_GRAVITY);

Note: When a device is at rest, the output of the gravity sensor should be identical to that of the accelerometer.

Using the Gyroscope


The gyroscope measures the rate of rotation in rad/s around a device's x, y, and z axis. The following code shows you how to get an instance of the default gyroscope:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_GYROSCOPE);

Usually, the output of the gyroscope is integrated over time to calculate a rotation describing the change of angles over the timestep. For example:

// Create a constant to convert nanoseconds to seconds.
private static final float NS2S = 1.0f / 1000000000.0f;
private final float[] deltaRotationVector = new float[4]();
private float timestamp;

public void onSensorChanged(SensorEvent event) {
  // This timestep's delta rotation to be multiplied by the current rotation
  // after computing it from the gyro sample data.
  if (timestamp != 0) {
    final float dT = (event.timestamp - timestamp) * NS2S;
    // Axis of the rotation sample, not normalized yet.
    float axisX = event.values[0];
    float axisY = event.values[1];
    float axisZ = event.values[2];

    // Calculate the angular speed of the sample
    float omegaMagnitude = sqrt(axisX*axisX + axisY*axisY + axisZ*axisZ);

    // Normalize the rotation vector if it's big enough to get the axis
    // (that is, EPSILON should represent your maximum allowable margin of error)
    if (omegaMagnitude > EPSILON) {
      axisX /= omegaMagnitude;
      axisY /= omegaMagnitude;
      axisZ /= omegaMagnitude;
    }

    // Integrate around this axis with the angular speed by the timestep
    // in order to get a delta rotation from this sample over the timestep
    // We will convert this axis-angle representation of the delta rotation
    // into a quaternion before turning it into the rotation matrix.
    float thetaOverTwo = omegaMagnitude * dT / 2.0f;
    float sinThetaOverTwo = sin(thetaOverTwo);
    float cosThetaOverTwo = cos(thetaOverTwo);
    deltaRotationVector[0] = sinThetaOverTwo * axisX;
    deltaRotationVector[1] = sinThetaOverTwo * axisY;
    deltaRotationVector[2] = sinThetaOverTwo * axisZ;
    deltaRotationVector[3] = cosThetaOverTwo;
  }
  timestamp = event.timestamp;
  float[] deltaRotationMatrix = new float[9];
  SensorManager.getRotationMatrixFromVector(deltaRotationMatrix, deltaRotationVector);
    // User code should concatenate the delta rotation we computed with the current rotation
    // in order to get the updated rotation.
    // rotationCurrent = rotationCurrent * deltaRotationMatrix;
   }
}

Using the Uncalibrated Gyroscope

In addition to the rates of rotation, the uncalibrated gyroscope also provides the estimated drift around each axis. The following code shows you how to get an instance of the default uncalibrated gyroscope:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_GYROSCOPE_UNCALIBRATED);
Using the Linear Accelerometer

The linear acceleration sensor provides you with a three-dimensional vector representing acceleration along each device axis, excluding gravity. The following code shows you how to get an instance of the default linear acceleration sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_LINEAR_ACCELERATION);

Using the Rotation Vector Sensor


The rotation vector represents the orientation of the device as a combination of an angle and an axis, in which the device has rotated through an angle θ around an axis (x, y, or z). The following code shows you how to get an instance of the default rotation vector sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_ROTATION_VECTOR);

Using the Significant Motion Sensor

The following code shows you how to get an instance of the default significant motion sensor and how to register an event listener:

private SensorManager mSensorManager;
private Sensor mSensor;
private TriggerEventListener mTriggerEventListener;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_SIGNIFICANT_MOTION);

mTriggerEventListener = new TriggerEventListener() {
    @Override
    public void onTrigger(TriggerEvent event) {
        // Do work
    }
};

mSensorManager.requestTriggerSensor(mTriggerEventListener, mSensor);

Using the Step Counter Sensor


The step counter sensor provides the number of steps taken by the user since the last reboot while the sensor was activated. The step counter has more latency (up to 10 seconds) but more accuracy than the step detector sensor. The following code shows you how to get an instance of the default step counter sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_STEP_COUNTER);

Using the Step Detector Sensor


The step detector sensor triggers an event each time the user takes a step. The latency is expected to be below 2 seconds. The following code shows you how to get an instance of the default step detector sensor:

private SensorManager mSensorManager;
private Sensor mSensor;
...
mSensorManager = (SensorManager) getSystemService(Context.SENSOR_SERVICE);
mSensor = mSensorManager.getDefaultSensor(Sensor.TYPE_STEP_DETECTOR);
基于开源大模型的教学实训智能体软件,帮助教师生成课前备课设计、课后检测问答,提升效率与效果,提供学生全时在线练习与指导,实现教学相长。 智能教学辅助系统 这是一个智能教学辅助系统的前端项目,基于 Vue3+TypeScript 开发,使用 Ant Design Vue 作为 UI 组件库。 功能模块 用户模块 登录/注册功能,支持学生和教师角色 毛玻璃效果的登录界面 教师模块 备课与设计:根据课程大纲自动设计教学内容 考核内容生成:自动生成多样化考核题目及参考答案 学情数据分析:自动化检测学生答案,提供数据分析 学生模块 在线学习助手:结合教学内容解答问题 实时练习评测助手:生成随练题目并纠错 管理模块 用户管理:管理员/教师/学生等用户基本管理 课件资源管理:按学科列表管理教师备课资源 大屏概览:使用统计、效率指数、学习效果等 技术栈 Vue3 TypeScript Pinia 状态管理 Ant Design Vue 组件库 Axios 请求库 ByteMD 编辑器 ECharts 图表库 Monaco 编辑器 双主题支持(专业科技风/暗黑风) 开发指南 # 安装依赖 npm install # 启动开发服务器 npm run dev # 构建生产版本 npm run build 简介 本项目旨在开发一个基于开源大模型的教学实训智能体软件,帮助教师生成课前备课设计、课后检测问答,提升效率与效果,提供学生全时在线练习与指导,实现教学相长。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值