Hi,
I understand that you want to create waypoints from gyro and accelerometer data which involves sensor fusion, noise filtering, and double integration of acceleration to get position. Here is a concise step-by-step process:
- Apply filters to gyro and accelerometer data to reduce noise.
- Use gyro data to track the orientation of the object.
- Subtract gravity from the accelerometer data.
- Convert acceleration from the body frame to the inertial frame using the orientation data.
- Integrate the acceleration to obtain velocity.
- Integrate the velocity to obtain position.
- Create waypoints based on significant position changes.
Here is a sample code snippet for the same:
% Initialize state variables
prevVelocity = [0; 0; 0];
prevPosition = [0; 0; 0];
waypoints = [];
% Loop through sensor data
for i = 1:length(sensorData)
% Filter and transform sensor data
orientation = getOrientation(sensorData(i).gyro);
accelInertial = transformAcceleration(sensorData(i).accel, orientation);
% Integrate for velocity and position
deltaTime = sensorData(i).deltaTime;
velocity = prevVelocity + accelInertial * deltaTime;
position = prevPosition + velocity * deltaTime;
% Update waypoints
if isNewWaypoint(position, waypoints)
waypoints = [waypoints; position'];
end
% Update state for next iteration
prevVelocity = velocity;
prevPosition = position;
end
function isNew = isNewWaypoint(position, waypoints)
isNew = isempty(waypoints) || norm(position - waypoints(end, :)) > threshold;
end
This is a simplified representation and assumes you have functions like `getOrientation` and `transformAcceleration` to process gyro and accelerometer data, respectively. In practice, you'd need to handle sensor calibration, noise, and drift, and possibly use additional data sources to correct for accumulated errors.
For more information you can refer following articles for more information:
