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