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matlabbe
2026-06-04 10:02:52 -07:00
parent cb50b6f21b
commit cf6dfeb800
1 changed files with 125 additions and 69 deletions
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corelib/test/test_rtabmap_integration.cpp
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@@ -822,43 +822,72 @@ TEST_F(RtabmapIntegrationFixture, PR2_Scan2D_Stereo)
const std::string dbPath = testDataPath("pr2_scan2d_stereo_sample_15s.db"); const std::string dbPath = testDataPath("pr2_scan2d_stereo_sample_15s.db");
SKIP_IF_MISSING(dbPath); SKIP_IF_MISSING(dbPath);
ParametersMap rtabmapParams = baseRtabmapParams(); // Iterate over the BA-capable optimizers built into this rtabmap: CI
rtabmapParams[Parameters::kMemUseOdomFeatures()] = "true"; // containers ship with different combos (e.g. only ceres+toro), so each
ParametersMap odomParams = baseOdometryParams(); // variant is skipped when its optimizer is unavailable.
struct Variant { Optimizer::Type opt; const char * label; };
const std::vector<Variant> variants = {
{Optimizer::kTypeG2O, "g2o" },
{Optimizer::kTypeGTSAM, "gtsam"},
{Optimizer::kTypeCeres, "ceres"},
};
// passOdomDataToRtabmap=true: rtabmap reuses the keypoints/descriptors int variantsTested = 0;
// extracted during odometry (paired with Mem/UseOdomFeatures=true above). for(const Variant & v : variants)
const ReplayResult result = replayDatabase(dbPath, rtabmapParams, odomParams, {
/*useStoredOdomAsGuess=*/true, if(!Optimizer::isAvailable(v.opt))
/*passOdomDataToRtabmap=*/true); {
std::cerr << "[skip] optimizer " << v.label << " not available\n";
continue;
}
SCOPED_TRACE(std::string("variant=") + v.label);
const std::string strategy = uNumber2Str(static_cast<int>(v.opt));
EXPECT_GT(result.framesRead, 0); ParametersMap rtabmapParams = baseRtabmapParams();
EXPECT_EQ(0, result.odomLost) << "Odometry should never lose tracking"; rtabmapParams[Parameters::kMemUseOdomFeatures()] = "true";
EXPECT_EQ(27, result.finalGlobalGraphSize); rtabmapParams[Parameters::kOptimizerStrategy()] = strategy;
EXPECT_GE(result.proximityDetections, 1) rtabmapParams[Parameters::kVisBundleAdjustment()] = strategy;
<< "PR2 2D-scan dataset should produce proximity detections"; ParametersMap odomParams = baseOdometryParams();
// Observed: empty 489-555, obstacle 4851-5202. Wide bounds because the odomParams[Parameters::kOdomF2MBundleAdjustment()] = strategy;
// graph optimizer and visual odom drift differ per platform/optimizer.
EXPECT_GE(result.gridEmptyCells, 400); // passOdomDataToRtabmap=true: rtabmap reuses the keypoints/descriptors
EXPECT_LE(result.gridEmptyCells, 650); // extracted during odometry (paired with Mem/UseOdomFeatures=true above).
EXPECT_GE(result.gridObstacleCells, 4800); const ReplayResult result = replayDatabase(dbPath, rtabmapParams, odomParams,
EXPECT_LE(result.gridObstacleCells, 5300); /*useStoredOdomAsGuess=*/true,
/*passOdomDataToRtabmap=*/true,
/*goldenStampedGroundTruth=*/nullptr,
/*frameStride=*/1,
/*runLabel=*/v.label);
EXPECT_GT(result.framesRead, 0);
EXPECT_EQ(0, result.odomLost)
<< v.label << ": Odometry should never lose tracking";
EXPECT_EQ(27, result.finalGlobalGraphSize) << v.label;
EXPECT_GE(result.proximityDetections, 1)
<< v.label << ": PR2 2D-scan dataset should produce proximity detections";
// Observed: empty 489-555, obstacle 4851-5202. Wide bounds because the
// graph optimizer and visual odom drift differ per platform/optimizer.
EXPECT_GE(result.gridEmptyCells, 400) << v.label;
EXPECT_LE(result.gridEmptyCells, 650) << v.label;
EXPECT_GE(result.gridObstacleCells, 4800) << v.label;
EXPECT_LE(result.gridObstacleCells, 5300) << v.label;
#ifdef RTABMAP_OCTOMAP #ifdef RTABMAP_OCTOMAP
// Observed: empty 1805-1902, obstacle 21502-22383. Bounds are wide // Observed: empty 1805-1902, obstacle 21502-22383. Bounds are wide
// because without g2o (OdomF2M/BundleAdjustment disabled) visual // to absorb per-BA-backend visual-odom drift.
// odometry drifts a bit differently run-to-run, which propagates into EXPECT_GE(result.octomapEmptyCells, 1700) << v.label;
// the assembled occupancy grid. EXPECT_LE(result.octomapEmptyCells, 2100) << v.label;
EXPECT_GE(result.octomapEmptyCells, 1700); EXPECT_GE(result.octomapObstacleCells, 21000) << v.label;
EXPECT_LE(result.octomapEmptyCells, 2100); EXPECT_LE(result.octomapObstacleCells, 23000) << v.label;
EXPECT_GE(result.octomapObstacleCells, 21000);
EXPECT_LE(result.octomapObstacleCells, 23000);
#endif #endif
// Stereo F2M visual odom + visual loop closure -- observed RMSE ~3 cm, // Stereo F2M visual odom + visual loop closure -- observed RMSE ~3 cm,
// 5 cm bound gives ~50% headroom for run-to-run feature variance. // 5 cm bound gives ~50% headroom for run-to-run feature variance.
ASSERT_GE(result.translationalRmseFinal, 0.0f) ASSERT_GE(result.translationalRmseFinal, 0.0f)
<< "No Gt/translational_rmse in stats (ground truth missing?)"; << v.label << ": No Gt/translational_rmse in stats (ground truth missing?)";
EXPECT_LT(result.translationalRmseFinal, 0.05f) EXPECT_LT(result.translationalRmseFinal, 0.05f)
<< "Final trajectory RMSE = " << result.translationalRmseFinal << " m"; << v.label << " Final trajectory RMSE = " << result.translationalRmseFinal << " m";
++variantsTested;
}
ASSERT_GT(variantsTested, 0) << "no BA-capable optimizer was available";
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -991,44 +1020,71 @@ TEST_F(RtabmapIntegrationFixture, PR2_Scan2D_RGBD)
const std::string dbPath = testDataPath("pr2_scan2d_rgbd_sample_15s.db"); const std::string dbPath = testDataPath("pr2_scan2d_rgbd_sample_15s.db");
SKIP_IF_MISSING(dbPath); SKIP_IF_MISSING(dbPath);
ParametersMap rtabmapParams = baseRtabmapParams(); // Iterate over the BA-capable optimizers built into this rtabmap.
rtabmapParams[Parameters::kMemUseOdomFeatures()] = "true"; struct Variant { Optimizer::Type opt; const char * label; };
ParametersMap odomParams = baseOdometryParams(); const std::vector<Variant> variants = {
{Optimizer::kTypeG2O, "g2o" },
{Optimizer::kTypeGTSAM, "gtsam"},
{Optimizer::kTypeCeres, "ceres"},
};
// passOdomDataToRtabmap=true: rtabmap reuses the keypoints/descriptors int variantsTested = 0;
// extracted during odometry (paired with Mem/UseOdomFeatures=true above). for(const Variant & v : variants)
const ReplayResult result = replayDatabase(dbPath, rtabmapParams, odomParams, {
/*useStoredOdomAsGuess=*/false, if(!Optimizer::isAvailable(v.opt))
/*passOdomDataToRtabmap=*/true); {
std::cerr << "[skip] optimizer " << v.label << " not available\n";
continue;
}
SCOPED_TRACE(std::string("variant=") + v.label);
const std::string strategy = uNumber2Str(static_cast<int>(v.opt));
EXPECT_GT(result.framesRead, 0); ParametersMap rtabmapParams = baseRtabmapParams();
EXPECT_EQ(0, result.odomLost) << "Odometry should never lose tracking"; rtabmapParams[Parameters::kMemUseOdomFeatures()] = "true";
EXPECT_EQ(21, result.finalGlobalGraphSize); rtabmapParams[Parameters::kOptimizerStrategy()] = strategy;
EXPECT_GE(result.proximityDetections, 1) rtabmapParams[Parameters::kVisBundleAdjustment()] = strategy;
<< "PR2 2D-scan dataset should produce proximity detections"; ParametersMap odomParams = baseOdometryParams();
// Observed: empty 2696-3048, obstacle 4339-4937. Wide bounds absorb odomParams[Parameters::kOdomF2MBundleAdjustment()] = strategy;
// platform-level FP differences in the visual loop-closure path.
EXPECT_GE(result.gridEmptyCells, 2600); // passOdomDataToRtabmap=true: rtabmap reuses the keypoints/descriptors
EXPECT_LE(result.gridEmptyCells, 3200); // extracted during odometry (paired with Mem/UseOdomFeatures=true above).
EXPECT_GE(result.gridObstacleCells, 4200); const ReplayResult result = replayDatabase(dbPath, rtabmapParams, odomParams,
EXPECT_LE(result.gridObstacleCells, 5100); /*useStoredOdomAsGuess=*/false,
/*passOdomDataToRtabmap=*/true,
/*goldenStampedGroundTruth=*/nullptr,
/*frameStride=*/1,
/*runLabel=*/v.label);
EXPECT_GT(result.framesRead, 0);
EXPECT_EQ(0, result.odomLost)
<< v.label << ": Odometry should never lose tracking";
EXPECT_EQ(21, result.finalGlobalGraphSize) << v.label;
EXPECT_GE(result.proximityDetections, 1)
<< v.label << ": PR2 2D-scan dataset should produce proximity detections";
// Observed: empty 2696-3048, obstacle 4339-4937. Wide bounds absorb
// platform-level FP differences in the visual loop-closure path.
EXPECT_GE(result.gridEmptyCells, 2600) << v.label;
EXPECT_LE(result.gridEmptyCells, 3200) << v.label;
EXPECT_GE(result.gridObstacleCells, 4200) << v.label;
EXPECT_LE(result.gridObstacleCells, 5100) << v.label;
#ifdef RTABMAP_OCTOMAP #ifdef RTABMAP_OCTOMAP
// Observed: empty 6072-8037, obstacle 39924-44130. Bounds are wide // Observed: empty 6072-8037, obstacle 39924-44130. Bounds are wide
// because visual odometry drifts a bit differently run-to-run across // to absorb per-BA-backend visual-odom drift.
// platforms (different OpenCV versions and g2o-vs-no-g2o BA), which EXPECT_GE(result.octomapEmptyCells, 5500) << v.label;
// propagates into the assembled occupancy grid. EXPECT_LE(result.octomapEmptyCells, 8500) << v.label;
EXPECT_GE(result.octomapEmptyCells, 5500); EXPECT_GE(result.octomapObstacleCells, 38000) << v.label;
EXPECT_LE(result.octomapEmptyCells, 8500); EXPECT_LE(result.octomapObstacleCells, 44500) << v.label;
EXPECT_GE(result.octomapObstacleCells, 38000);
EXPECT_LE(result.octomapObstacleCells, 44500);
#endif #endif
// RGB-D F2M visual odom + visual loop closure -- observed RMSE ~13 cm // RGB-D F2M visual odom + visual loop closure -- observed RMSE ~13 cm
// (less stable than the stereo/ICP paths), 20 cm bound gives ~50% // (less stable than the stereo/ICP paths), 20 cm bound gives ~50%
// headroom for visual-only loop-closure variability. // headroom for visual-only loop-closure variability.
ASSERT_GE(result.translationalRmseFinal, 0.0f) ASSERT_GE(result.translationalRmseFinal, 0.0f)
<< "No Gt/translational_rmse in stats (ground truth missing?)"; << v.label << ": No Gt/translational_rmse in stats (ground truth missing?)";
EXPECT_LT(result.translationalRmseFinal, 0.20f) EXPECT_LT(result.translationalRmseFinal, 0.20f)
<< "Final trajectory RMSE = " << result.translationalRmseFinal << " m"; << v.label << " Final trajectory RMSE = " << result.translationalRmseFinal << " m";
++variantsTested;
}
ASSERT_GT(variantsTested, 0) << "no BA-capable optimizer was available";
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -1952,9 +2008,9 @@ TEST_F(RtabmapIntegrationFixture, AppearanceOnly_PrecisionRecall)
<< ", FP=" << acceptedFp << ")\n"; << ", FP=" << acceptedFp << ")\n";
} }
EXPECT_GE(recallAt100p, 0.9f) EXPECT_GE(recallAt100p, 0.85f)
<< detectorLabel << " recall@100%P=" << recallAt100p << detectorLabel << " recall@100%P=" << recallAt100p
<< " is below 0.9 (sortedTP=" << tp << ", sortedFP=" << fp << ")"; << " is below 0.85 (sortedTP=" << tp << ", sortedFP=" << fp << ")";
++detectorsTested; ++detectorsTested;
} // end for(tfIdfUsed) } // end for(tfIdfUsed)