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showIMUPredictionErrors

Visualizes absolute values of IMU prediction errors

Since R2024a

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    Syntax

    showIMUPredictionErrors(params)
    showIMUPredictionErrors(params,Name=Value)
    ax = showIMUPredictionErrors(___)

    Description

    showIMUPredictionErrors(params) visualizes the absolute values of prediction errors for the camera-IMU calibration parameters.

    showIMUPredictionErrors(params,Name=Value) specifies one or more name-value arguments.

    ax = showIMUPredictionErrors(___) returns axes that the IMU prediction errors are plotted on.

    Examples

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    Input Arguments
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    Estimated camera-to-IMU calibration parameters, specified as a cameraIMUParameters object.
    
        
    Use the estimateCameraIMUTransform function to get the estimated camera-to-IMU
            calibration parameters.
    
    
    Name-Value Arguments
    Specify optional pairs of arguments as
      Name1=Value1,...,NameN=ValueN, where Name is
      the argument name and Value is the corresponding value.
      Name-value arguments must appear after other arguments, but the order of the
      pairs does not matter.
    
    Example: showIMUPredictionErrors(params,Mode="percentage")
    
            
    Parent axes, specified as a vector of six Axes object handles. By default, the showIMUPredictionErrors
              function plots the estimates in the a new figure.
    
          
    
            
    Prediction error value mode, specified as either "absolute" or
                "percentage":
    

    • "absolute" — View the absolute value of the prediction
                    error.
    • "percentage" — View the prediction error as a percentage
                    with respect to motion. The motion is computed from the optimized poses. This
                    mode is ideal if the sensor setup between successive images varies from pair to
                    pair. If there are large variations in movement that cause large errors,
                    normalizing the errors using the percentage mode enable you to visualize the
                    errors more easily.
    

    
          
    
            
    Plotted IMU prediction error threshold value, specified as a six-element vector or
              as a two-element vector.
    
            
    If Threshold is a six-element vector, it is in the form
                [TR_X, TR_Y, TR_Z,
                ROT_X, ROT_Y, ROT_Z].
                TR_X, TR_Y, and TR_Z are
              the translation error thresholds along the x, y,
              and z axes, in meters. ROT_X,
                ROT_Y, and ROT_Z are the rotation error
              thresholds about the x, y, and
                z axes, in radians.
    
            
    If Threshold is a two-element vector, it is in the form
                [TR_Th, ROT_Th]. TR_Th and
                ROT_Th are the translation and rotation error thresholds for the
                xyz-axes.
    
          
    Output Arguments
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    Axes graphic handle, returned as an Axes object. This object contains the properties of the figure that you plot the transformation onto.
    Tips
    • If the IMU prediction errors are consistently large throughout the dataset, consider
          capturing calibration data again with a different motion profile.
    Version History
    Introduced in R2024a
    See Also
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