cartographer探秘第四章之代码解析（八） --- 生成地图
2024-05-18 17:52:43
本次阅读的源码为 release-1.0 版本的代码
https://github.com/googlecartographer/cartographer_ros/tree/release-1.0
https://github.com/googlecartographer/cartographer/tree/release-1.0
也可以下载我上传的 全套工作空间的代码，包括 protobuf, cartographer, cartographer_ros, ceres,
https://download.csdn.net/download/tiancailx/11224156，现在上传资源自己不能选下载需要的积分。。。完全靠系统。
本篇文章写了如何从激光雷达数据写成二维栅格地图的过程。
1 local_trajectory_builder_2d类
// cartographer/mapping/internal/2d/local_trajectory_builder_2d.cc
std::unique_ptr<LocalTrajectoryBuilder2D::MatchingResult>
LocalTrajectoryBuilder2D::AddAccumulatedRangeData()
{std::unique_ptr<InsertionResult> insertion_result =InsertIntoSubmap(time, range_data_in_local, gravity_aligned_range_data,pose_estimate, gravity_alignment.rotation());
}std::unique_ptr<LocalTrajectoryBuilder2D::InsertionResult>
LocalTrajectoryBuilder2D::InsertIntoSubmap(const common::Time time, const sensor::RangeData& range_data_in_local,const sensor::RangeData& gravity_aligned_range_data,const transform::Rigid3d& pose_estimate,const Eigen::Quaterniond& gravity_alignment) {// Querying the active submaps must be done here before calling// InsertRangeData() since the queried values are valid for next insertion.std::vector<std::shared_ptr<const Submap2D>> insertion_submaps;for (const std::shared_ptr<Submap2D>& submap : active_submaps_.submaps()) {insertion_submaps.push_back(submap);}active_submaps_.InsertRangeData(range_data_in_local);
}2 ActiveSubmaps2D类 与 Submap2D类
void ActiveSubmaps2D::InsertRangeData(const sensor::RangeData& range_data) {for (auto& submap : submaps_) {// 将雷达数据写入submapsubmap->InsertRangeData(range_data, range_data_inserter_.get());}if (submaps_.back()->num_range_data() == options_.num_range_data()) {// 当range data 数量达到配置的值时，将新建个submapAddSubmap(range_data.origin.head<2>());}
}void ActiveSubmaps2D::AddSubmap(const Eigen::Vector2f& origin) {if (submaps_.size() > 1) {// This will crop the finished Submap before inserting a new Submap to// reduce peak memory usage a bit.// 新建时，如果submap的个数为2,则需要先将第一个submap设置成finish，并从active submap中删掉FinishSubmap();}// 新建一个active submapsubmaps_.push_back(common::make_unique<Submap2D>(origin, std::unique_ptr<Grid2D>(static_cast<Grid2D*>(CreateGrid(origin).release()))));LOG(INFO) << "Added submap " << matching_submap_index_ + submaps_.size();
}std::unique_ptr<GridInterface> ActiveSubmaps2D::CreateGrid(const Eigen::Vector2f& origin) {constexpr int kInitialSubmapSize = 100;float resolution = options_.grid_options_2d().resolution();// 新建一个ProbalityGridreturn common::make_unique<ProbabilityGrid>(MapLimits(resolution,origin.cast<double>() + 0.5 * kInitialSubmapSize * resolution *Eigen::Vector2d::Ones(),CellLimits(kInitialSubmapSize, kInitialSubmapSize)));
}void Submap2D::InsertRangeData(const sensor::RangeData& range_data,const RangeDataInserterInterface* range_data_inserter) {CHECK(grid_);CHECK(!finished());range_data_inserter->Insert(range_data, grid_.get());set_num_range_data(num_range_data() + 1);
}void ActiveSubmaps2D::FinishSubmap() {Submap2D* submap = submaps_.front().get();submap->Finish();++matching_submap_index_;submaps_.erase(submaps_.begin());
}void Submap2D::Finish() {CHECK(grid_);CHECK(!finished());// 计算裁剪栅格地图grid_ = grid_->ComputeCroppedGrid();set_finished(true);
}//cartographer/cartographer/mapping/submaps.hvoid set_finished(bool finished) { finished_ = finished; }// cartographer/cartographer/mapping/2d/probability_grid.cc
std::unique_ptr<Grid2D> ProbabilityGrid::ComputeCroppedGrid() const {Eigen::Array2i offset;CellLimits cell_limits;ComputeCroppedLimits(&offset, &cell_limits);const double resolution = limits().resolution();const Eigen::Vector2d max =limits().max() - resolution * Eigen::Vector2d(offset.y(), offset.x());std::unique_ptr<ProbabilityGrid> cropped_grid =common::make_unique<ProbabilityGrid>(MapLimits(resolution, max, cell_limits));for (const Eigen::Array2i& xy_index : XYIndexRangeIterator(cell_limits)) {if (!IsKnown(xy_index + offset)) continue;cropped_grid->SetProbability(xy_index, GetProbability(xy_index + offset));}return std::unique_ptr<Grid2D>(cropped_grid.release());
}3 ProbabilityGridRangeDataInserter2D类
只在cartographer/cartographer/mapping/internal/2d/local_trajectory_builder_2d.h 中的 ActiveSubmaps2D 进行初始化时构造一次，初始化时计算 hit_table_ 与 miss_table_ ；
// cartographer/cartographer/mapping/2d/probability_grid_range_data_inserter_2d.ccProbabilityGridRangeDataInserter2D::ProbabilityGridRangeDataInserter2D(const proto::ProbabilityGridRangeDataInserterOptions2D& options): options_(options),hit_table_(ComputeLookupTableToApplyCorrespondenceCostOdds(Odds(options.hit_probability()))),miss_table_(ComputeLookupTableToApplyCorrespondenceCostOdds(Odds(options.miss_probability()))) {}void ProbabilityGridRangeDataInserter2D::Insert(const sensor::RangeData& range_data, GridInterface* const grid) const {ProbabilityGrid* const probability_grid = static_cast<ProbabilityGrid*>(grid);// By not finishing the update after hits are inserted, we give hits priority// (i.e. no hits will be ignored because of a miss in the same cell).CastRays(range_data, hit_table_, miss_table_, options_.insert_free_space(),CHECK_NOTNULL(probability_grid));probability_grid->FinishUpdate();
}// cartographer/cartographer/mapping/2d/probability_grid_range_data_inserter_2d.h
class ProbabilityGridRangeDataInserter2D : public RangeDataInserterInterface {// Inserts 'range_data' into 'probability_grid'.virtual void Insert(const sensor::RangeData& range_data,GridInterface* grid) const override;private:const proto::ProbabilityGridRangeDataInserterOptions2D options_;const std::vector<uint16> hit_table_;const std::vector<uint16> miss_table_;
};3.1 hit_table_ 与 miss_table_ 的初始化
调用了两个在文件probability_values.h中定义的函数。 其中函数CorrespondenceCostToValue是将float类型的数据转换为uint16类型，并将输入从区间 [kMinCorrespondenceCost,kMaxCorrespondenceCost] 映射到 [1,32767]。
函数ProbabilityToCorrespondenceCost实际上是对输入概率值取反，这意味着如果我们的输入描述的是栅格单元的占用概率，那么实际存储的则是栅格单元空闲的概率。
std::vector<uint16> ComputeLookupTableToApplyCorrespondenceCostOdds(float odds/*0.55*/) {std::vector<uint16> result;result.push_back(// 22327 + 32768(kUpdateMarker) = 55095CorrespondenceCostToValue( // 0.6451 --> 22327ProbabilityToCorrespondenceCost( // 0.6451 = 1 - 0.3548ProbabilityFromOdds(odds) )) + // 0.3548 = 0.55/(0.55+1)kUpdateMarker); // constexpr uint16 kUpdateMarker = 1u << 15; // 32768for (int cell = 1; cell != 32768; ++cell) {result.push_back(CorrespondenceCostToValue(ProbabilityToCorrespondenceCost(ProbabilityFromOdds(odds * Odds( // a/(1-a)CorrespondenceCostToProbability( // 1- b(*kValueToCorrespondenceCost)[cell] ) )))) +kUpdateMarker); }return result;
}3.2 CastRays()
cartographer/cartographer/mapping/internal/2d/ray_casting.cc
void CastRays(const sensor::RangeData& range_data,const std::vector<uint16>& hit_table,const std::vector<uint16>& miss_table,const bool insert_free_space,ProbabilityGrid* const probability_grid) {GrowAsNeeded(range_data, probability_grid);const MapLimits& limits = probability_grid->limits();const double superscaled_resolution = limits.resolution() / kSubpixelScale;const MapLimits superscaled_limits(superscaled_resolution, limits.max(),CellLimits(limits.cell_limits().num_x_cells * kSubpixelScale,limits.cell_limits().num_y_cells * kSubpixelScale));const Eigen::Array2i begin =superscaled_limits.GetCellIndex(range_data.origin.head<2>());// Compute and add the end points.std::vector<Eigen::Array2i> ends;ends.reserve(range_data.returns.size());for (const Eigen::Vector3f& hit : range_data.returns) {ends.push_back(superscaled_limits.GetCellIndex(hit.head<2>()));probability_grid->ApplyLookupTable(ends.back() / kSubpixelScale, hit_table);}if (!insert_free_space) {return;}// Now add the misses.for (const Eigen::Array2i& end : ends) {CastRay(begin, end, miss_table, probability_grid);}// Finally, compute and add empty rays based on misses in the range data.for (const Eigen::Vector3f& missing_echo : range_data.misses) {CastRay(begin, superscaled_limits.GetCellIndex(missing_echo.head<2>()),miss_table, probability_grid);}
}
3.3 ProbabilityGrid::ApplyLookupTable()
//cartographer/cartographer/mapping/2d/probability_grid.cc// Applies the 'odds' specified when calling ComputeLookupTableToApplyOdds()
// to the probability of the cell at 'cell_index' if the cell has not already
// been updated. Multiple updates of the same cell will be ignored until
// FinishUpdate() is called. Returns true if the cell was updated.
//
// If this is the first call to ApplyOdds() for the specified cell, its value
// will be set to probability corresponding to 'odds'.
bool ProbabilityGrid::ApplyLookupTable(const Eigen::Array2i& cell_index,const std::vector<uint16>& table) {DCHECK_EQ(table.size(), kUpdateMarker);const int flat_index = ToFlatIndex(cell_index);uint16* cell = &(*mutable_correspondence_cost_cells())[flat_index];if (*cell >= kUpdateMarker) {return false;}mutable_update_indices()->push_back(flat_index);*cell = table[*cell];DCHECK_GE(*cell, kUpdateMarker);mutable_known_cells_box()->extend(cell_index.matrix());return true;
}3.4 CastRay()
// Factor for subpixel accuracy of start and end point.
constexpr int kSubpixelScale = 1000;// We divide each pixel in kSubpixelScale x kSubpixelScale subpixels. 'begin'
// and 'end' are coordinates at subpixel precision. We compute all pixels in
// which some part of the line segment connecting 'begin' and 'end' lies.
void CastRay(const Eigen::Array2i& begin, const Eigen::Array2i& end,const std::vector<uint16>& miss_table,ProbabilityGrid* const probability_grid) {// For simplicity, we order 'begin' and 'end' by their x coordinate.if (begin.x() > end.x()) {CastRay(end, begin, miss_table, probability_grid);return;}CHECK_GE(begin.x(), 0);CHECK_GE(begin.y(), 0);CHECK_GE(end.y(), 0);// Special case: We have to draw a vertical line in full pixels, as 'begin'// and 'end' have the same full pixel x coordinate.if (begin.x() / kSubpixelScale == end.x() / kSubpixelScale) {Eigen::Array2i current(begin.x() / kSubpixelScale,std::min(begin.y(), end.y()) / kSubpixelScale);const int end_y = std::max(begin.y(), end.y()) / kSubpixelScale;for (; current.y() <= end_y; ++current.y()) {probability_grid->ApplyLookupTable(current, miss_table);}return;}const int64 dx = end.x() - begin.x();const int64 dy = end.y() - begin.y();const int64 denominator = 2 * kSubpixelScale * dx;// The current full pixel coordinates. We begin at 'begin'.Eigen::Array2i current = begin / kSubpixelScale;// To represent subpixel centers, we use a factor of 2 * 'kSubpixelScale' in// the denominator.// +-+-+-+ -- 1 = (2 * kSubpixelScale) / (2 * kSubpixelScale)// | | | |// +-+-+-+// | | | |// +-+-+-+ -- top edge of first subpixel = 2 / (2 * kSubpixelScale)// | | | | -- center of first subpixel = 1 / (2 * kSubpixelScale)// +-+-+-+ -- 0 = 0 / (2 * kSubpixelScale)// The center of the subpixel part of 'begin.y()' assuming the// 'denominator', i.e., sub_y / denominator is in (0, 1).int64 sub_y = (2 * (begin.y() % kSubpixelScale) + 1) * dx;// The distance from the from 'begin' to the right pixel border, to be divided// by 2 * 'kSubpixelScale'.const int first_pixel =2 * kSubpixelScale - 2 * (begin.x() % kSubpixelScale) - 1;// The same from the left pixel border to 'end'.const int last_pixel = 2 * (end.x() % kSubpixelScale) + 1;// The full pixel x coordinate of 'end'.const int end_x = std::max(begin.x(), end.x()) / kSubpixelScale;// Move from 'begin' to the next pixel border to the right.sub_y += dy * first_pixel;if (dy > 0) {while (true) {probability_grid->ApplyLookupTable(current, miss_table);while (sub_y > denominator) {sub_y -= denominator;++current.y();probability_grid->ApplyLookupTable(current, miss_table);}++current.x();if (sub_y == denominator) {sub_y -= denominator;++current.y();}if (current.x() == end_x) {break;}// Move from one pixel border to the next.sub_y += dy * 2 * kSubpixelScale;}// Move from the pixel border on the right to 'end'.sub_y += dy * last_pixel;probability_grid->ApplyLookupTable(current, miss_table);while (sub_y > denominator) {sub_y -= denominator;++current.y();probability_grid->ApplyLookupTable(current, miss_table);}CHECK_NE(sub_y, denominator);CHECK_EQ(current.y(), end.y() / kSubpixelScale);return;}// Same for lines non-ascending in y coordinates.while (true) {probability_grid->ApplyLookupTable(current, miss_table);while (sub_y < 0) {sub_y += denominator;--current.y();probability_grid->ApplyLookupTable(current, miss_table);}++current.x();if (sub_y == 0) {sub_y += denominator;--current.y();}if (current.x() == end_x) {break;}sub_y += dy * 2 * kSubpixelScale;}sub_y += dy * last_pixel;probability_grid->ApplyLookupTable(current, miss_table);while (sub_y < 0) {sub_y += denominator;--current.y();probability_grid->ApplyLookupTable(current, miss_table);}CHECK_NE(sub_y, 0);CHECK_EQ(current.y(), end.y() / kSubpixelScale);
}void GrowAsNeeded(const sensor::RangeData& range_data,ProbabilityGrid* const probability_grid) {Eigen::AlignedBox2f bounding_box(range_data.origin.head<2>());constexpr float kPadding = 1e-6f;for (const Eigen::Vector3f& hit : range_data.returns) {bounding_box.extend(hit.head<2>());}for (const Eigen::Vector3f& miss : range_data.misses) {bounding_box.extend(miss.head<2>());}probability_grid->GrowLimits(bounding_box.min() -kPadding * Eigen::Vector2f::Ones());probability_grid->GrowLimits(bounding_box.max() +kPadding * Eigen::Vector2f::Ones());
}3.5 FinishUpdate()
cartographer/cartographer/mapping/2d/grid_2d.cc
// Finishes the update sequence.
void Grid2D::FinishUpdate() {while (!update_indices_.empty()) {DCHECK_GE(correspondence_cost_cells_[update_indices_.back()],kUpdateMarker);correspondence_cost_cells_[update_indices_.back()] -= kUpdateMarker;update_indices_.pop_back();}
}4 map_limits.h
struct CellLimits {CellLimits() = default;CellLimits(int init_num_x_cells, int init_num_y_cells): num_x_cells(init_num_x_cells), num_y_cells(init_num_y_cells) {}explicit CellLimits(const proto::CellLimits& cell_limits): num_x_cells(cell_limits.num_x_cells()),num_y_cells(cell_limits.num_y_cells()) {}int num_x_cells = 0;int num_y_cells = 0;
};// Defines the limits of a grid map. This class must remain inlined for
// performance reasons.
class MapLimits {private:// Returns the cell size in meters. All cells are square and the resolution is the length of one side.double resolution_; // Returns the corner of the limits, i.e., all pixels have positions with smaller coordinates.Eigen::Vector2d max_; // Returns the limits of the grid in number of cells.CellLimits cell_limits_;
};map_limits 记录了地图的各种信息，分辨率，物理世界坐标的最大值（左上角的栅格最大），栅格的x, y方向的格子数量。
max_ 为该栅格在物理世界中的坐标，不是栅格的坐标。
5 Grid2D
class Grid2D : public GridInterface {public:explicit Grid2D(const MapLimits& limits, float min_correspondence_cost,float max_correspondence_cost);explicit Grid2D(const proto::Grid2D& proto);// Returns the limits of this Grid2D.const MapLimits& limits() const { return limits_; }// Finishes the update sequence.void FinishUpdate();// Returns the correspondence cost of the cell with 'cell_index'.float GetCorrespondenceCost(const Eigen::Array2i& cell_index) const;// Returns the minimum possible correspondence cost.float GetMinCorrespondenceCost() const { return min_correspondence_cost_; }// Returns the maximum possible correspondence cost.float GetMaxCorrespondenceCost() const { return max_correspondence_cost_; }// Returns true if the probability at the specified index is known.bool IsKnown(const Eigen::Array2i& cell_index) const;// Fills in 'offset' and 'limits' to define a subregion of that contains all// known cells.void ComputeCroppedLimits(Eigen::Array2i* const offset,CellLimits* const limits) const;// Grows the map as necessary to include 'point'. This changes the meaning of// these coordinates going forward. This method must be called immediately// after 'FinishUpdate', before any calls to 'ApplyLookupTable'.virtual void GrowLimits(const Eigen::Vector2f& point);virtual std::unique_ptr<Grid2D> ComputeCroppedGrid() const = 0;virtual proto::Grid2D ToProto() const;virtual bool DrawToSubmapTexture(proto::SubmapQuery::Response::SubmapTexture* const texture,transform::Rigid3d local_pose) const = 0;protected:const std::vector<uint16>& correspondence_cost_cells() const {return correspondence_cost_cells_;}const std::vector<int>& update_indices() const { return update_indices_; }const Eigen::AlignedBox2i& known_cells_box() const {return known_cells_box_;}std::vector<uint16>* mutable_correspondence_cost_cells() {return &correspondence_cost_cells_;}std::vector<int>* mutable_update_indices() { return &update_indices_; }Eigen::AlignedBox2i* mutable_known_cells_box() { return &known_cells_box_; }// Converts a 'cell_index' into an index into 'cells_'.int ToFlatIndex(const Eigen::Array2i& cell_index) const;private:// 地图信息MapLimits limits_;// 栅格地图每个栅格的概率值std::vector<uint16> correspondence_cost_cells_; // 概率最小值，最大值float min_correspondence_cost_;float max_correspondence_cost_;// std::vector<int> update_indices_;// Bounding box of known cells to efficiently compute cropping limits.Eigen::AlignedBox2i known_cells_box_;
};
// Returns the correspondence cost of the cell with 'cell_index'.
float Grid2D::GetCorrespondenceCost(const Eigen::Array2i& cell_index) const {if (!limits().Contains(cell_index)) return kMaxCorrespondenceCost;return ValueToCorrespondenceCost(correspondence_cost_cells()[ToFlatIndex(cell_index)]);
}const std::vector<uint16>& correspondence_cost_cells() const {return correspondence_cost_cells_;}int Grid2D::ToFlatIndex(const Eigen::Array2i& cell_index) const {CHECK(limits_.Contains(cell_index)) << cell_index;return limits_.cell_limits().num_x_cells * cell_index.y() + cell_index.x();
}// Converts a uint16 (which may or may not have the update marker set) to a
// correspondence cost in the range [kMinCorrespondenceCost,
// kMaxCorrespondenceCost].
inline float ValueToCorrespondenceCost(const uint16 value) {return (*kValueToCorrespondenceCost)[value];
}const std::vector<float>* const kValueToCorrespondenceCost =PrecomputeValueToCorrespondenceCost().release();std::unique_ptr<std::vector<float>> PrecomputeValueToCorrespondenceCost() {return PrecomputeValueToBoundedFloat(kUnknownCorrespondenceValue, kMaxCorrespondenceCost,kMinCorrespondenceCost, kMaxCorrespondenceCost);
}std::unique_ptr<std::vector<float>> PrecomputeValueToBoundedFloat(const uint16 unknown_value, const float unknown_result,const float lower_bound, const float upper_bound) {auto result = common::make_unique<std::vector<float>>();// Repeat two times, so that both values with and without the update marker// can be converted to a probability.for (int repeat = 0; repeat != 2; ++repeat) {for (int value = 0; value != 32768; ++value) {result->push_back(SlowValueToBoundedFloat(value, unknown_value, unknown_result, lower_bound, upper_bound));}}return result;
}// 0 is unknown, [1, 32767] maps to [lower_bound, upper_bound].
float SlowValueToBoundedFloat(const uint16 value, const uint16 unknown_value,const float unknown_result,const float lower_bound,const float upper_bound) {CHECK_GE(value, 0);CHECK_LE(value, 32767);if (value == unknown_value) return unknown_result;const float kScale = (upper_bound - lower_bound) / 32766.f;return value * kScale + (lower_bound - kScale);
}REFERENCES
cartographer 生成子图 https://blog.csdn.net/xiaoma_bk/article/details/83063389
查找表与占用栅格更新 http://gaoyichao.com/Xiaotu/?book=Cartographer%E6%BA%90%E7%A0%81%E8%A7%A3%E8%AF%BB&title=%E6%9F%A5%E6%89%BE%E8%A1%A8%E4%B8%8E%E5%8D%A0%E7%94%A8%E6%A0%85%E6%A0%BC%E6%9B%B4%E6%96%B0
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