Remove intensities - they are unused in SLAM. (#247)

cartographer/mapping_2d/global_trajectory_builder.cc

@@ -37,7 +37,7 @@ void GlobalTrajectoryBuilder::AddRangefinderData(
     const sensor::PointCloud& ranges) {
   std::unique_ptr<LocalTrajectoryBuilder::InsertionResult> insertion_result =
       local_trajectory_builder_.AddHorizontalRangeData(
-          time, sensor::RangeData{origin, ranges, {}, {}});
+          time, sensor::RangeData{origin, ranges, {}});
   if (insertion_result != nullptr) {
     sparse_pose_graph_->AddScan(
         insertion_result->time, insertion_result->tracking_to_tracking_2d,

cartographer/mapping_2d/local_trajectory_builder.cc

@@ -83,7 +83,7 @@ sensor::RangeData LocalTrajectoryBuilder::TransformAndFilterRangeData(
     const sensor::RangeData& range_data) const {
   // Drop any returns below the minimum range and convert returns beyond the
   // maximum range into misses.
-  sensor::RangeData returns_and_misses{range_data.origin, {}, {}, {}};
+  sensor::RangeData returns_and_misses{range_data.origin, {}, {}};
   for (const Eigen::Vector3f& hit : range_data.returns) {
     const float range = (hit - range_data.origin).norm();
     if (range >= options_.laser_min_range()) {

cartographer/mapping_2d/map_limits_test.cc

@@ -69,7 +69,7 @@ TEST(MapLimitsTest, ComputeMapLimits) {
           Eigen::Vector3f::Zero(),
           {Eigen::Vector3f(-30.f, 1.f, 0.f), Eigen::Vector3f(50.f, -10.f, 0.f)},
           {}},
-      Compress(sensor::RangeData{Eigen::Vector3f::Zero(), {}, {}, {}}), nullptr,
+      Compress(sensor::RangeData{Eigen::Vector3f::Zero(), {}, {}}), nullptr,
       transform::Rigid3d::Identity()};
   const mapping::TrajectoryNode trajectory_node{&constant_data,
                                                 transform::Rigid3d::Identity()};

cartographer/mapping_2d/sparse_pose_graph.cc

@@ -99,7 +99,7 @@ void SparsePoseGraph::AddScan(
 
   constant_node_data_->push_back(mapping::TrajectoryNode::ConstantData{
       time, range_data_in_pose,
-      Compress(sensor::RangeData{Eigen::Vector3f::Zero(), {}, {}, {}}), submaps,
+      Compress(sensor::RangeData{Eigen::Vector3f::Zero(), {}, {}}), submaps,
       tracking_to_pose});
   trajectory_nodes_.push_back(mapping::TrajectoryNode{
       &constant_node_data_->back(), optimized_pose,
@@ -294,25 +294,30 @@ void SparsePoseGraph::WaitForAllComputations() {
   common::MutexLocker locker(&mutex_);
   const int num_finished_scans_at_start =
       constraint_builder_.GetNumFinishedScans();
-  while (!locker.AwaitWithTimeout([this]() REQUIRES(mutex_) {
+  while (!locker.AwaitWithTimeout(
-    return static_cast<size_t>(constraint_builder_.GetNumFinishedScans()) ==
+      [this]() REQUIRES(mutex_) {
-           trajectory_nodes_.size();
+        return static_cast<size_t>(constraint_builder_.GetNumFinishedScans()) ==
-  }, common::FromSeconds(1.))) {
+               trajectory_nodes_.size();
+      },
+      common::FromSeconds(1.))) {
     std::ostringstream progress_info;
     progress_info << "Optimizing: " << std::fixed << std::setprecision(1)
-                  << 100. * (constraint_builder_.GetNumFinishedScans() -
+                  << 100. *
-                             num_finished_scans_at_start) /
+                         (constraint_builder_.GetNumFinishedScans() -
+                          num_finished_scans_at_start) /
                          (trajectory_nodes_.size() -
-                          num_finished_scans_at_start) << "%...";
+                          num_finished_scans_at_start)
+                  << "%...";
     std::cout << "\r\x1b[K" << progress_info.str() << std::flush;
   }
   std::cout << "\r\x1b[KOptimizing: Done.     " << std::endl;
-  constraint_builder_.WhenDone([this, &notification](
+  constraint_builder_.WhenDone(
-      const sparse_pose_graph::ConstraintBuilder::Result& result) {
+      [this, &notification](
-    constraints_.insert(constraints_.end(), result.begin(), result.end());
+          const sparse_pose_graph::ConstraintBuilder::Result& result) {
-    common::MutexLocker locker(&mutex_);
+        constraints_.insert(constraints_.end(), result.begin(), result.end());
-    notification = true;
+        common::MutexLocker locker(&mutex_);
-  });
+        notification = true;
+      });
   locker.Await([&notification]() { return notification; });
 }
 
@@ -346,13 +351,13 @@ void SparsePoseGraph::RunOptimization() {
       const mapping::Submaps* trajectory =
           trajectory_nodes_[i].constant_data->trajectory;
       if (extrapolation_transforms.count(trajectory) == 0) {
-        extrapolation_transforms[trajectory] =
+        extrapolation_transforms[trajectory] = transform::Rigid3d(
-            transform::Rigid3d(ExtrapolateSubmapTransforms(submap_transforms_,
+            ExtrapolateSubmapTransforms(submap_transforms_, *trajectory)
-                                                           *trajectory).back() *
+                .back() *
-                               ExtrapolateSubmapTransforms(
+            ExtrapolateSubmapTransforms(optimized_submap_transforms_,
-                                   optimized_submap_transforms_, *trajectory)
+                                        *trajectory)
-                                   .back()
+                .back()
-                                   .inverse());
+                .inverse());
       }
       trajectory_nodes_[i].pose =
           extrapolation_transforms[trajectory] * trajectory_nodes_[i].pose;

cartographer/mapping_3d/kalman_local_trajectory_builder.cc

@@ -91,7 +91,7 @@ KalmanLocalTrajectoryBuilder::AddRangefinderData(
   const transform::Rigid3f tracking_delta =
       first_pose_prediction_.inverse() * pose_prediction.cast<float>();
   const sensor::RangeData range_data_in_first_tracking =
-      sensor::TransformRangeData(sensor::RangeData{origin, ranges, {}, {}},
+      sensor::TransformRangeData(sensor::RangeData{origin, ranges, {}},
                                  tracking_delta);
   for (const Eigen::Vector3f& hit : range_data_in_first_tracking.returns) {
     const Eigen::Vector3f delta = hit - range_data_in_first_tracking.origin;

cartographer/mapping_3d/submaps.cc

@@ -174,7 +174,7 @@ void InsertSegmentsIntoProbabilityGrid(const std::vector<RaySegment>& segments,
 // information.
 sensor::RangeData FilterRangeDataByMaxRange(const sensor::RangeData& range_data,
                                             const float max_range) {
-  sensor::RangeData result{range_data.origin, {}, {}, {}};
+  sensor::RangeData result{range_data.origin, {}, {}};
   for (const Eigen::Vector3f& hit : range_data.returns) {
     if ((hit - range_data.origin).norm() <= max_range) {
       result.returns.push_back(hit);

cartographer/sensor/compressed_point_cloud.cc

@@ -35,67 +35,6 @@ constexpr int kBitsPerCoordinate = 10;
 constexpr int kCoordinateMask = (1 << kBitsPerCoordinate) - 1;
 constexpr int kMaxBitsPerDirection = 23;
 
-// Compressed point cloud into a vector and optionally returns mapping from
-// compressed indices to original indices.
-std::vector<int32> Compress(const PointCloud& point_cloud,
-                            std::vector<int>* new_to_old = nullptr) {
-  // Distribute points into blocks.
-  struct RasterPoint {
-    Eigen::Array3i point;
-    int index;
-  };
-  using Blocks = mapping_3d::HybridGridBase<std::vector<RasterPoint>>;
-  Blocks blocks(kPrecision, Eigen::Vector3f::Zero());
-  int num_blocks = 0;
-  CHECK_LE(point_cloud.size(), std::numeric_limits<int>::max());
-  for (int point_index = 0; point_index < static_cast<int>(point_cloud.size());
-       ++point_index) {
-    const Eigen::Vector3f& point = point_cloud[point_index];
-    CHECK_LT(point.cwiseAbs().maxCoeff() / kPrecision,
-             1 << kMaxBitsPerDirection)
-        << "Point out of bounds: " << point;
-    Eigen::Array3i raster_point;
-    Eigen::Array3i block_coordinate;
-    for (int i = 0; i < 3; ++i) {
-      raster_point[i] = common::RoundToInt(point[i] / kPrecision);
-      block_coordinate[i] = raster_point[i] >> kBitsPerCoordinate;
-      raster_point[i] &= kCoordinateMask;
-    }
-    auto* const block = blocks.mutable_value(block_coordinate);
-    num_blocks += block->empty();
-    block->push_back({raster_point, point_index});
-  }
-
-  if (new_to_old != nullptr) {
-    new_to_old->clear();
-    new_to_old->reserve(point_cloud.size());
-  }
-
-  // Encode blocks.
-  std::vector<int32> result;
-  result.reserve(4 * num_blocks + point_cloud.size());
-  for (Blocks::Iterator it(blocks); !it.Done(); it.Next(), --num_blocks) {
-    const auto& raster_points = it.GetValue();
-    CHECK_LE(raster_points.size(), std::numeric_limits<int32>::max());
-    result.push_back(raster_points.size());
-    const Eigen::Array3i block_coordinate = it.GetCellIndex();
-    result.push_back(block_coordinate.x());
-    result.push_back(block_coordinate.y());
-    result.push_back(block_coordinate.z());
-    for (const RasterPoint& raster_point : raster_points) {
-      result.push_back((((raster_point.point.z() << kBitsPerCoordinate) +
-                         raster_point.point.y())
-                        << kBitsPerCoordinate) +
-                       raster_point.point.x());
-      if (new_to_old != nullptr) {
-        new_to_old->push_back(raster_point.index);
-      }
-    }
-  }
-  CHECK_EQ(num_blocks, 0);
-  return result;
-}
-
 }  // namespace
 
 CompressedPointCloud::ConstIterator::ConstIterator(
@@ -158,18 +97,58 @@ void CompressedPointCloud::ConstIterator::ReadNextPoint() {
 }
 
 CompressedPointCloud::CompressedPointCloud(const PointCloud& point_cloud)
-    : point_data_(Compress(point_cloud)), num_points_(point_cloud.size()) {}
+    : num_points_(point_cloud.size()) {
+  // Distribute points into blocks.
+  struct RasterPoint {
+    Eigen::Array3i point;
+    int index;
+  };
+  using Blocks = mapping_3d::HybridGridBase<std::vector<RasterPoint>>;
+  Blocks blocks(kPrecision, Eigen::Vector3f::Zero());
+  int num_blocks = 0;
+  CHECK_LE(point_cloud.size(), std::numeric_limits<int>::max());
+  for (int point_index = 0; point_index < static_cast<int>(point_cloud.size());
+       ++point_index) {
+    const Eigen::Vector3f& point = point_cloud[point_index];
+    CHECK_LT(point.cwiseAbs().maxCoeff() / kPrecision,
+             1 << kMaxBitsPerDirection)
+        << "Point out of bounds: " << point;
+    Eigen::Array3i raster_point;
+    Eigen::Array3i block_coordinate;
+    for (int i = 0; i < 3; ++i) {
+      raster_point[i] = common::RoundToInt(point[i] / kPrecision);
+      block_coordinate[i] = raster_point[i] >> kBitsPerCoordinate;
+      raster_point[i] &= kCoordinateMask;
+    }
+    auto* const block = blocks.mutable_value(block_coordinate);
+    num_blocks += block->empty();
+    block->push_back({raster_point, point_index});
+  }
+
+  // Encode blocks.
+  point_data_.reserve(4 * num_blocks + point_cloud.size());
+  for (Blocks::Iterator it(blocks); !it.Done(); it.Next(), --num_blocks) {
+    const auto& raster_points = it.GetValue();
+    CHECK_LE(raster_points.size(), std::numeric_limits<int32>::max());
+    point_data_.push_back(raster_points.size());
+    const Eigen::Array3i block_coordinate = it.GetCellIndex();
+    point_data_.push_back(block_coordinate.x());
+    point_data_.push_back(block_coordinate.y());
+    point_data_.push_back(block_coordinate.z());
+    for (const RasterPoint& raster_point : raster_points) {
+      point_data_.push_back((((raster_point.point.z() << kBitsPerCoordinate) +
+                         raster_point.point.y())
+                        << kBitsPerCoordinate) +
+                       raster_point.point.x());
+    }
+  }
+  CHECK_EQ(num_blocks, 0);
+}
 
 CompressedPointCloud::CompressedPointCloud(const std::vector<int32>& point_data,
                                            size_t num_points)
     : point_data_(point_data), num_points_(num_points) {}
 
-CompressedPointCloud CompressedPointCloud::CompressAndReturnOrder(
-    const PointCloud& point_cloud, std::vector<int>* new_to_old) {
-  return CompressedPointCloud(Compress(point_cloud, new_to_old),
-                              point_cloud.size());
-}
-
 bool CompressedPointCloud::empty() const { return num_points_ == 0; }
 
 size_t CompressedPointCloud::size() const { return num_points_; }

cartographer/sensor/compressed_point_cloud.h

@@ -40,12 +40,6 @@ class CompressedPointCloud {
   CompressedPointCloud() : num_points_(0) {}
   explicit CompressedPointCloud(const PointCloud& point_cloud);
 
-  // Returns a compressed point cloud and further returns a mapping 'new_to_old'
-  // from the compressed indices to the original indices, i.e., conceptually
-  // compressed[i] = point_cloud[new_to_old[i]].
-  static CompressedPointCloud CompressAndReturnOrder(
-      const PointCloud& point_cloud, std::vector<int>* new_to_old);
-
   // Returns decompressed point cloud.
   PointCloud Decompress() const;
 
@@ -59,8 +53,8 @@ class CompressedPointCloud {
  private:
   CompressedPointCloud(const std::vector<int32>& point_data, size_t num_points);
 
-  const std::vector<int32> point_data_;
+  std::vector<int32> point_data_;
-  const size_t num_points_;
+  size_t num_points_;
 };
 
 // Forward iterator for compressed point clouds.

cartographer/sensor/compressed_point_cloud_test.cc

@@ -116,21 +116,6 @@ TEST(CompressPointCloudTest, CompressesNoGaps) {
   }
 }
 
-TEST(CompressPointCloudTest, CompressesAndReturnsOrder) {
-  PointCloud point_cloud = {
-      Eigen::Vector3f(1.f, 0.f, 0.f), Eigen::Vector3f(-10.f, 0.f, 0.f),
-      Eigen::Vector3f(1.f, 0.f, 0.f), Eigen::Vector3f(-10.f, 0.f, 0.f)};
-  std::vector<int> new_to_old;
-  CompressedPointCloud compressed =
-      CompressedPointCloud::CompressAndReturnOrder(point_cloud, &new_to_old);
-  EXPECT_EQ(point_cloud.size(), new_to_old.size());
-  int i = 0;
-  for (const Eigen::Vector3f& point : compressed) {
-    EXPECT_THAT(point, ApproximatelyEquals(point_cloud[new_to_old[i]]));
-    ++i;
-  }
-}
-
 }  // namespace
 }  // namespace sensor
 }  // namespace cartographer

cartographer/sensor/proto/sensor.proto

@@ -74,7 +74,4 @@ message RangeData {
   optional transform.proto.Vector3f origin = 1;
   optional PointCloud point_cloud = 2;
   optional PointCloud missing_echo_point_cloud = 3;
-
-  // Reflectivity values of point_cloud or empty.
-  repeated int32 reflectivity = 4 [packed = true];
 }

cartographer/sensor/range_data.cc

@@ -22,21 +22,6 @@
 namespace cartographer {
 namespace sensor {
 
-namespace {
-
-// Reorders reflectivities according to index mapping.
-std::vector<uint8> ReorderReflectivities(
-    const std::vector<uint8>& reflectivities,
-    const std::vector<int>& new_to_old) {
-  std::vector<uint8> reordered(reflectivities.size());
-  for (size_t i = 0; i < reordered.size(); ++i) {
-    reordered[i] = reflectivities[new_to_old[i]];
-  }
-  return reordered;
-}
-
-}  // namespace
-
 PointCloud ToPointCloud(const proto::LaserScan& proto) {
   return ToPointCloudWithIntensities(proto).points;
 }
@@ -77,8 +62,6 @@ proto::RangeData ToProto(const RangeData& range_data) {
   *proto.mutable_origin() = transform::ToProto(range_data.origin);
   *proto.mutable_point_cloud() = ToProto(range_data.returns);
   *proto.mutable_missing_echo_point_cloud() = ToProto(range_data.misses);
-  std::copy(range_data.reflectivities.begin(), range_data.reflectivities.end(),
-            RepeatedFieldBackInserter(proto.mutable_reflectivity()));
   return proto;
 }
 
@@ -87,8 +70,6 @@ RangeData FromProto(const proto::RangeData& proto) {
       transform::ToEigen(proto.origin()), ToPointCloud(proto.point_cloud()),
       ToPointCloud(proto.missing_echo_point_cloud()),
   };
-  std::copy(proto.reflectivity().begin(), proto.reflectivity().end(),
-            std::back_inserter(range_data.reflectivities));
   return range_data;
 }
 
@@ -98,7 +79,6 @@ RangeData TransformRangeData(const RangeData& range_data,
       transform * range_data.origin,
       TransformPointCloud(range_data.returns, transform),
       TransformPointCloud(range_data.misses, transform),
-      range_data.reflectivities,
   };
 }
 
@@ -109,21 +89,16 @@ RangeData CropRangeData(const RangeData& range_data, const float min_z,
 }
 
 CompressedRangeData Compress(const RangeData& range_data) {
-  std::vector<int> new_to_old;
-  CompressedPointCloud compressed_returns =
-      CompressedPointCloud::CompressAndReturnOrder(range_data.returns,
-                                                   &new_to_old);
   return CompressedRangeData{
-      range_data.origin, std::move(compressed_returns),
+      range_data.origin, CompressedPointCloud(range_data.returns),
       CompressedPointCloud(range_data.misses),
-      ReorderReflectivities(range_data.reflectivities, new_to_old)};
+  };
 }
 
 RangeData Decompress(const CompressedRangeData& compressed_range_data) {
   return RangeData{compressed_range_data.origin,
                    compressed_range_data.returns.Decompress(),
-                   compressed_range_data.misses.Decompress(),
+                   compressed_range_data.misses.Decompress()};
-                   compressed_range_data.reflectivities};
 }
 
 }  // namespace sensor

cartographer/sensor/range_data.h

@@ -33,9 +33,6 @@ struct RangeData {
   Eigen::Vector3f origin;
   PointCloud returns;
   PointCloud misses;
-
-  // Reflectivity value of returns.
-  std::vector<uint8> reflectivities;
 };
 
 // Builds a PointCloud of returns from 'proto', dropping any beams with ranges
@@ -67,9 +64,6 @@ struct CompressedRangeData {
   Eigen::Vector3f origin;
   CompressedPointCloud returns;
   CompressedPointCloud misses;
-
-  // Reflectivity value of returns.
-  std::vector<uint8> reflectivities;
 };
 
 CompressedRangeData Compress(const RangeData& range_data);

cartographer/sensor/range_data_test.cc

@@ -74,43 +74,30 @@ TEST(LaserTest, ToPointCloudWithInfinityAndNaN) {
   EXPECT_TRUE(point_cloud[1].isApprox(Eigen::Vector3f(-3.f, 0.f, 0.f), 1e-6));
 }
 
-// Custom matcher for pair<eigen::Vector3f, int> entries.
+// Custom matcher for Eigen::Vector3f entries.
-MATCHER_P(PairApproximatelyEquals, expected,
+MATCHER_P(ApproximatelyEquals, expected,
           string("is equal to ") + PrintToString(expected)) {
-  return (arg.first - expected.first).isZero(0.001f) &&
+  return (arg - expected).isZero(0.001f);
-         arg.second == expected.second;
 }
 
 TEST(RangeDataTest, Compression) {
+  const std::vector<Eigen::Vector3f> returns = {Eigen::Vector3f(0, 1, 2),
+                                                Eigen::Vector3f(4, 5, 6),
+                                                Eigen::Vector3f(0, 1, 2)};
   const RangeData range_data = {
-      Eigen::Vector3f(1, 1, 1),
+      Eigen::Vector3f(1, 1, 1), returns, {Eigen::Vector3f(7, 8, 9)}};
-      {Eigen::Vector3f(0, 1, 2), Eigen::Vector3f(4, 5, 6),
-       Eigen::Vector3f(0, 1, 2)},
-      {Eigen::Vector3f(7, 8, 9)},
-      {1, 2, 3}};
   const RangeData actual = Decompress(Compress(range_data));
   EXPECT_TRUE(actual.origin.isApprox(Eigen::Vector3f(1, 1, 1), 1e-6));
   EXPECT_EQ(3, actual.returns.size());
   EXPECT_EQ(1, actual.misses.size());
-  EXPECT_EQ(actual.returns.size(), actual.reflectivities.size());
   EXPECT_TRUE(actual.misses[0].isApprox(Eigen::Vector3f(7, 8, 9), 0.001f));
 
-  // Returns and their corresponding reflectivities will be reordered, so we
+  // Returns will be reordered, so we compare in an unordered manner.
-  // pair them up into a vector, and compare in an unordered manner.
+  EXPECT_EQ(3, actual.returns.size());
-  std::vector<std::pair<Eigen::Vector3f, int>> pairs;
+  EXPECT_THAT(actual.returns,
-  for (size_t i = 0; i < actual.returns.size(); ++i) {
+              Contains(ApproximatelyEquals(Eigen::Vector3f(0, 1, 2))));
-    pairs.emplace_back(actual.returns[i], actual.reflectivities[i]);
+  EXPECT_THAT(actual.returns,
-  }
+              Contains(ApproximatelyEquals(Eigen::Vector3f(4, 5, 6))));
-  EXPECT_EQ(3, pairs.size());
-  EXPECT_THAT(pairs,
-              Contains(PairApproximatelyEquals(std::pair<Eigen::Vector3f, int>(
-                  Eigen::Vector3f(0, 1, 2), 1))));
-  EXPECT_THAT(pairs,
-              Contains(PairApproximatelyEquals(std::pair<Eigen::Vector3f, int>(
-                  Eigen::Vector3f(0, 1, 2), 3))));
-  EXPECT_THAT(pairs,
-              Contains(PairApproximatelyEquals(std::pair<Eigen::Vector3f, int>(
-                  Eigen::Vector3f(4, 5, 6), 2))));
 }
 
 }  // namespace