Compute alignment RANSAC max_error from RMS stddev and chi-square #3664
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ahojnnes
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Oct 17, 2025
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| const double trace = pose_prior.position_covariance.trace(); | ||
| if (trace > 0.0) { | ||
| const double rms_stddev = std::sqrt(trace / 3.0); | ||
| sum_rms_stddev += rms_stddev; | ||
| ++num_valid_covs; | ||
| } |
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What do you think about the following? This would be more robust to outliers?
std::vector<double> rms_vars;
for (const auto& [_, pose_prior] : pose_priors_) {
if (pose_prior.IsCovarianceValid()) {
const double trace = pose_prior.position_covariance.trace();
if (trace > 0.0) {
const double rms_stddev = trace / 3.0;
rms_vars.push_back(rms_var);
}
}
}
ransac_options.max_error = std::sqrt(kChiSquare95ThreeDof * Median(rms_vars));
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The previous method is sensitive to priors with extreme covariances, producing unstable RANSAC thresholds.
This PR computes the mean RMS stddev from valid covariances and scale it by sqrt(chi-square 95% quantile, dof=3)
to yield an approximate 95% 3D confidence radius.