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thresholded mu to avoid case mu = 0 in TLS. improved verbosity handling

release/4.3a0
lcarlone 2022-01-12 21:31:22 -05:00
parent e0082d746c
commit 859e4cb37a
2 changed files with 21 additions and 6 deletions
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25
gtsam/nonlinear/GncOptimizer.h
View File

@ -206,9 +206,11 @@ class GTSAM_EXPORT GncOptimizer {
std::cout << "GNC Optimizer stopped because all measurements are already known to be inliers or outliers"
<< std::endl;
}
if (params_.verbosity >= GncParameters::Verbosity::MU) {
std::cout << "mu: " << mu << std::endl;
}
if (params_.verbosity >= GncParameters::Verbosity::VALUES) {
result.print("result\n");
std::cout << "mu: " << mu << std::endl;
}
return result;
}
@ -217,12 +219,16 @@ class GTSAM_EXPORT GncOptimizer {
for (iter = 0; iter < params_.maxIterations; iter++) {
// display info
if (params_.verbosity >= GncParameters::Verbosity::VALUES) {
if (params_.verbosity >= GncParameters::Verbosity::MU) {
std::cout << "iter: " << iter << std::endl;
result.print("result\n");
std::cout << "mu: " << mu << std::endl;
}
if (params_.verbosity >= GncParameters::Verbosity::WEIGHTS) {
std::cout << "weights: " << weights_ << std::endl;
}
if (params_.verbosity >= GncParameters::Verbosity::VALUES) {
result.print("result\n");
}
// weights update
weights_ = calculateWeights(result, mu);
@ -253,10 +259,12 @@ class GTSAM_EXPORT GncOptimizer {
if (params_.verbosity >= GncParameters::Verbosity::SUMMARY) {
std::cout << "final iterations: " << iter << std::endl;
std::cout << "final mu: " << mu << std::endl;
std::cout << "final weights: " << weights_ << std::endl;
std::cout << "previous cost: " << prev_cost << std::endl;
std::cout << "current cost: " << cost << std::endl;
}
if (params_.verbosity >= GncParameters::Verbosity::WEIGHTS) {
std::cout << "final weights: " << weights_ << std::endl;
}
return result;
}
@ -291,6 +299,9 @@ class GTSAM_EXPORT GncOptimizer {
std::min(mu_init, barcSq_[k] / (2 * rk - barcSq_[k]) ) : mu_init;
}
}
if (mu_init >= 0 && mu_init < 1e-6)
mu_init = 1e-6; // if mu ~ 0 (but positive), that means we have measurements with large errors,
// i.e., rk > barcSq_[k] and rk very large, hence we threshold to 1e-6 to avoid mu = 0
return mu_init > 0 && !std::isinf(mu_init) ? mu_init : -1; // if mu <= 0 or mu = inf, return -1,
// which leads to termination of the main gnc loop. In this case, all residuals are already below the threshold
// and there is no need to robustify (TLS = least squares)
@ -338,8 +349,10 @@ class GTSAM_EXPORT GncOptimizer {
bool checkCostConvergence(const double cost, const double prev_cost) const {
bool costConverged = std::fabs(cost - prev_cost) / std::max(prev_cost, 1e-7)
< params_.relativeCostTol;
if (costConverged && params_.verbosity >= GncParameters::Verbosity::SUMMARY)
std::cout << "checkCostConvergence = true " << std::endl;
if (costConverged && params_.verbosity >= GncParameters::Verbosity::SUMMARY){
std::cout << "checkCostConvergence = true (prev. cost = " << prev_cost
<< ", curr. cost = " << cost << ")" << std::endl;
}
return costConverged;
}

2
gtsam/nonlinear/GncParams.h
View File

@ -48,6 +48,8 @@ class GTSAM_EXPORT GncParams {
enum Verbosity {
SILENT = 0,
SUMMARY,
MU,
WEIGHTS,
VALUES
};