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making some tests less flaky

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matlabbe
2026-05-24 22:39:04 -07:00
parent e9c0194546
commit 828a7ed100
5 changed files with 127 additions and 16 deletions
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corelib/test/test_rtabmap.cpp
+47 -7
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@@ -1017,6 +1017,14 @@ TEST_F(RtabmapFixture, RejectLastLoopClosureRemovesLinkAndResetsHypothesis)
// so mapCorrection collapses back to identity.
ParametersMap params = defaultRtabmapParams();
params[Parameters::kRGBDOptimizeMaxError()] = "0";
// TORO's default convergence epsilon (1e-5) stops the gradient descent
// while ~18 mm of correction still hasn't unwound. Tighten it so all
// three backends converge close enough to identity to satisfy the
// post-check below. Iterations stay at the default (100): bumping them
// further would let TORO reach ~1 mm, but the test's 1 cm bound is
// already comfortably above the ~6.5 mm TORO hits at 100 iterations
// with this epsilon, so the cheaper iteration budget is enough.
params[Parameters::kOptimizerEpsilon()] = "1e-10";
reinit(params);
process();
const int N1 = rtabmap_->getLastLocationId();
@@ -1039,8 +1047,14 @@ TEST_F(RtabmapFixture, RejectLastLoopClosureRemovesLinkAndResetsHypothesis)
{
EXPECT_NE(kv.second.type(), Link::kUserClosure);
}
// Graph re-optimized without the rejected link -> mapCorrection identity.
EXPECT_TRUE(rtabmap_->getMapCorrection().isIdentity());
// Graph re-optimized without the rejected link -> mapCorrection collapses
// back toward identity. The rejected loop disagreed with the odom chain
// by 1 m, so a 1 cm residual is 99% undone. (g2o / GTSAM hit zero; TORO
// is gradient-descent so its floor is non-zero - around 6.5 mm at the
// default 100 iterations with epsilon 1e-10. Transform::isIdentity() is
// bit-exact, so we check the norm instead.)
const Transform mc = rtabmap_->getMapCorrection();
EXPECT_LT(mc.getNorm(), 1e-2f) << "post-reject correction: " << mc.prettyPrint();
}
TEST_F(RtabmapFixture, RejectLastLoopClosureIsNoOpWhenNoLoopClosureExists)
@@ -1712,7 +1726,10 @@ TEST_F(RtabmapFixture, FollowLongPathWithIntermediateNodesRetrievesRealLtmNodes)
for(const auto & kv : rtabmap_->getPath())
{
const Signature * s = rtabmap_->getMemory()->getSignature(kv.first);
if(s) EXPECT_NE(s->getWeight(), -1) << "intermediate id=" << kv.first << " on path";
if(s)
{
EXPECT_NE(s->getWeight(), -1) << "intermediate id=" << kv.first << " on path";
}
}
// Walk back along the path. Path-follow advances and eventually reaches N1.
@@ -2918,8 +2935,12 @@ TEST(RtabmapTest, GlobalBundleAdjustmentRefinesPosesOnSynthScene)
/*align2D=*/false);
return std::make_pair(t_rmse, r_rmse);
};
const auto [tRmseBefore, rRmseBefore] = rmse(before);
const auto [tRmseAfter, rRmseAfter] = rmse(after);
const auto rmseBefore = rmse(before);
const auto rmseAfter = rmse(after);
const float tRmseBefore = rmseBefore.first;
const float rRmseBefore = rmseBefore.second;
const float tRmseAfter = rmseAfter.first;
const float rRmseAfter = rmseAfter.second;
// BA must reduce both translational and rotational RMSE toward GT, with
// the residual bounded by the measurement noise floor.
EXPECT_LT(tRmseAfter, tRmseBefore) << "BA must reduce translational RMSE";
@@ -3214,7 +3235,22 @@ TEST(RtabmapTest, LandmarkObservationsAcrossFramesShareSameLandmarkPose)
// Two frames both observe landmark id=42 at the same world location.
// Memory stores the landmark once (key=-42 in the graph) and links both
// frames to it.
//
// The default optimizer is built-dependent: GTSAM and g2o include the
// landmark as a graph variable; TORO ignores landmark constraints and
// won't expose -kLm in the optimized poses. Force a backend that
// supports landmarks; skip if none is available in this build.
int optimizerStrategy = -1;
if(Optimizer::isAvailable(Optimizer::kTypeGTSAM)) optimizerStrategy = Optimizer::kTypeGTSAM;
else if(Optimizer::isAvailable(Optimizer::kTypeG2O)) optimizerStrategy = Optimizer::kTypeG2O;
if(optimizerStrategy < 0)
{
GTEST_SKIP() << "neither GTSAM nor g2o is available; the default optimizer "
"(TORO/Ceres) does not include landmarks in the optimized graph";
}
ParametersMap params = defaultRtabmapParams();
params[Parameters::kOptimizerStrategy()] = uNumber2Str(optimizerStrategy);
params[Parameters::kOptimizerLandmarksIgnored()] = "false";
Rtabmap rtabmap;
rtabmap.init(params);
const cv::Mat cov = cv::Mat::eye(6, 6, CV_64FC1) * 0.01;
@@ -3657,8 +3693,12 @@ TEST(RtabmapTest, AggressiveLoopThresholdAcceptsBelowPrimaryThreshold)
return std::make_pair(id, high);
};
const auto [idAgg, highAgg] = runOnce(kAggressiveThr);
const auto [idPrim, highPrim] = runOnce(kLoopThr); // aggressive disabled (= primary)
const auto resultAgg = runOnce(kAggressiveThr);
const auto resultPrim = runOnce(kLoopThr); // aggressive disabled (= primary)
const int idAgg = resultAgg.first;
const float highAgg = resultAgg.second;
const int idPrim = resultPrim.first;
const float highPrim = resultPrim.second;
// Sanity: both invocations see the same Bayes peak (deterministic data).
EXPECT_NEAR(highAgg, highPrim, 1e-3);