KlabCMU / learned-map-prior

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Parameters configuration about TurtleBot dataset #3

Open zyw1515414231 opened 1 year ago

zyw1515414231 commented 1 year ago

hello, when testing on TurtleBot dataset, what parameters should I choose? '--filter-history-length' and '--data-kernel-len' should be set to 20, right? And how about the '--filter-update-rate'? Is it 60Hz or 100Hz? What's more, can you describe how to transform wheel odometry to right heading in detail? Thank you! Hope for your reply!

karnikram commented 1 year ago

Hi,

'--filter-history-length' and '--data-kernel-len' should be set to 20, right?

Yes.

And how about the '--filter-update-rate'? Is it 60Hz or 100Hz?

It is 100 Hz.

What's more, can you describe how to transform wheel odometry to right heading in detail?

To obtain heading from wheel odometry data we use a standard Madgwick filter such as this one. Once you have the heading, we apply a motion model as described in this code snippet:


def wheel_odom_motion_model(x_t0, odom, odometry_cov):
    current_heading_angle = x_t0[2]
    step_size = np.linalg.norm(odom[:2])
    step = np.array([step_size*np.cos(current_heading_angle), step_size*np.sin(current_heading_angle)])
    noise = sample(odometry_cov)
    step = step + np.random.normal(0,0.01)

    heading_delta = odom[2] + np.random.normal(0,0.01)

    x_t1 = np.zeros_like(x_t0)
    x_t1[:2] = x_t0[:2] + step

    x_t1[2] = current_heading_angle + heading_delta
    return x_t1

Hope this helps!