cartographer探秘第五章之 Cartographer 所用到的 C++11 新特性
2024-06-07 03:16:46
Caro的代码使用了大量的 C++11 新特性，这篇博客将对这些出现的特性进行汇总以及记录，我还没怎么用过C++11。
1 关键字:
constexpr: 在编译过程就能确定的常量(计算结果的表达式)
void Run() {constexpr double kTfBufferCacheTimeInSeconds = 10.;tf2_ros::Buffer tf_buffer{::ros::Duration(kTfBufferCacheTimeInSeconds)};tf2_ros::TransformListener tf(tf_buffer);// ...
}delete: 禁止使用该函数
// Wires up ROS topics to SLAM. 将ROS主题连接到SLAM。
class Node {public:Node(const NodeOptions& node_options,std::unique_ptr<cartographer::mapping::MapBuilderInterface> map_builder,tf2_ros::Buffer* tf_buffer);~Node();// = delete 禁止使用该函数, delete 可用于任何函数Node(const Node&) = delete;Node& operator=(const Node&) = delete;// ...
}explicit: 阻止隐式转换的发生
class SensorBridge {public:explicit SensorBridge(int num_subdivisions_per_laser_scan, const std::string& tracking_frame,double lookup_transform_timeout_sec, tf2_ros::Buffer* tf_buffer,::cartographer::mapping::TrajectoryBuilderInterface* trajectory_builder);// ...
}2 用到的C++11的标准函数:
std::move(): 将左值引用转变为右值引用
void Run() {// ...// move() 将左值引用转变为右值引用auto map_builder =cartographer::common::make_unique<cartographer::mapping::MapBuilder>(node_options.map_builder_options);Node node(node_options, std::move(map_builder), &tf_buffer);if (!FLAGS_load_state_filename.empty()) {node.LoadState(FLAGS_load_state_filename, FLAGS_load_frozen_state);}// ...
}std::tie()
void Run() {// ...NodeOptions node_options;TrajectoryOptions trajectory_options;std::tie(node_options, trajectory_options) =LoadOptions(FLAGS_configuration_directory, FLAGS_configuration_basename);// ...
}std::forward_as_tuple()
extrapolators_.emplace(std::piecewise_construct, std::forward_as_tuple(trajectory_id),std::forward_as_tuple(::cartographer::common::FromSeconds(kExtrapolationEstimationTimeSec),gravity_time_constant));std::tuple()
set::insert()
std::unique_ptr<>
#include <memory>std::mt19937 rng(0);
计算随机数的算法
std::prev
std::exp()，std::hypot()，std::abs()
candidate.score *=std::exp(-common::Pow2(std::hypot(candidate.x, candidate.y) *options_.translation_delta_cost_weight() +std::abs(candidate.orientation) *options_.rotation_delta_cost_weight()));std::max_element() , std::max()
const Candidate2D& best_candidate =*std::max_element(candidates.begin(), candidates.end());// A possible solution.
struct Candidate2D {Candidate2D(const int init_scan_index, const int init_x_index_offset,const int init_y_index_offset,const SearchParameters& search_parameters): scan_index(init_scan_index),x_index_offset(init_x_index_offset),y_index_offset(init_y_index_offset),x(-y_index_offset * search_parameters.resolution),y(-x_index_offset * search_parameters.resolution),orientation((scan_index - search_parameters.num_angular_perturbations) *search_parameters.angular_perturbation_step_size) {}// Index into the rotated scans vector.int scan_index = 0;// Linear offset from the initial pose.int x_index_offset = 0;int y_index_offset = 0;// Pose of this Candidate2D relative to the initial pose.double x = 0.;double y = 0.;double orientation = 0.;// Score, higher is better.float score = 0.f;bool operator<(const Candidate2D& other) const { return score < other.score; }bool operator>(const Candidate2D& other) const { return score > other.score; }
};std::sort() , std::greater
std::sort(candidates->begin(), candidates->end(), std::greater<Candidate2D>());std::bind std::placeholders : 占位符
const int trajectory_id = map_builder_->AddTrajectoryBuilder(expected_sensor_ids, trajectory_options.trajectory_builder_options,::std::bind(&MapBuilderBridge::OnLocalSlamResult, this,::std::placeholders::_1, ::std::placeholders::_2,::std::placeholders::_3, ::std::placeholders::_4,::std::placeholders::_5));std::function
// cartographer/cartographer/mapping/trajectory_builder_interface.h#include<functional>using LocalSlamResultCallback =std::function<void(int /* trajectory ID */, common::Time,transform::Rigid3d /* local pose estimate */,sensor::RangeData /* in local frame */,std::unique_ptr<const InsertionResult>)>;// cartographer/cartographer/mapping/map_builder_interface.husing LocalSlamResultCallback =TrajectoryBuilderInterface::LocalSlamResultCallback;// Creates a new trajectory builder and returns its index.virtual int AddTrajectoryBuilder(const std::set<SensorId>& expected_sensor_ids,const proto::TrajectoryBuilderOptions& trajectory_options,LocalSlamResultCallback local_slam_result_callback) = 0;// cartographer/cartographer/mapping/map_builder.hint AddTrajectoryBuilder(const std::set<SensorId> &expected_sensor_ids,const proto::TrajectoryBuilderOptions &trajectory_options,LocalSlamResultCallback local_slam_result_callback) override;范围for循环：for (const auto& entry : sensor_bridges_)
std::unordered_map<int, MapBuilderBridge::TrajectoryState>
MapBuilderBridge::GetTrajectoryStates() {std::unordered_map<int, TrajectoryState> trajectory_states;for (const auto& entry : sensor_bridges_) {const int trajectory_id = entry.first;const SensorBridge& sensor_bridge = *entry.second;std::shared_ptr<const TrajectoryState::LocalSlamData> local_slam_data;{cartographer::common::MutexLocker lock(&mutex_);if (trajectory_state_data_.count(trajectory_id) == 0) {continue;}local_slam_data = trajectory_state_data_.at(trajectory_id);}// Make sure there is a trajectory with 'trajectory_id'.CHECK_EQ(trajectory_options_.count(trajectory_id), 1);trajectory_states[trajectory_id] = {local_slam_data,map_builder_->pose_graph()->GetLocalToGlobalTransform(trajectory_id),sensor_bridge.tf_bridge().LookupToTracking(local_slam_data->time,trajectory_options_[trajectory_id].published_frame),trajectory_options_[trajectory_id]};}return trajectory_states;
}// -----------const int half_width = 1 << (7 - 1);
for (int x_offset : {0, half_width})
{cout << x_offset << endl;
}std::chrono
#include <chrono>// Time at which we last logged the rates of incoming sensor data.std::chrono::steady_clock::time_point last_logging_time_;3 容器类相关
3.1 vector
reserve() , emplace_back() , push_back() , back()
std::vector<DiscreteScan2D> DiscretizeScans(const MapLimits& map_limits, const std::vector<sensor::PointCloud>& scans,const Eigen::Translation2f& initial_translation) {std::vector<DiscreteScan2D> discrete_scans;discrete_scans.reserve(scans.size());for (const sensor::PointCloud& scan : scans) {discrete_scans.emplace_back();discrete_scans.back().reserve(scan.size());for (const Eigen::Vector3f& point : scan) {const Eigen::Vector2f translated_point =Eigen::Affine2f(initial_translation) * point.head<2>();discrete_scans.back().push_back(map_limits.GetCellIndex(translated_point));}}return discrete_scans;
}3.2 map
std::map()
#include <map>
#include <unordered_map>// These are keyed with 'trajectory_id'.std::map<int, ::cartographer::mapping::PoseExtrapolator> extrapolators_;std::unordered_map<int, TrajectorySensorSamplers> sensor_samplers_;
map::emplace() 用于直接构造和插入元素
3.3 set
std::set<>
#include <set> #include <unordered_set>// Adds a trajectory for offline processing, i.e. not listening to topics.int AddOfflineTrajectory(const std::set<cartographer::mapping::TrajectoryBuilderInterface::SensorId>&expected_sensor_ids,const TrajectoryOptions& options);// unordered_setstd::unordered_set<std::string> subscribed_topics_;4 其他:
GUARDED_BY()
MapBuilderBridge map_builder_bridge_ GUARDED_BY(mutex_);EXCLUDES()
std::unordered_map<int, TrajectoryState> GetTrajectoryStates() EXCLUDES(mutex_);type_traits: 模板元编程
#include <cstddef>
#include <memory>
#include <type_traits>
#include <utility>// Implementation of c++14's std::make_unique, taken from
// https://isocpp.org/files/papers/N3656.txt
template <class T>
struct _Unique_if {typedef std::unique_ptr<T> _Single_object;
};... : 可变参数模板
template <class T, class... Args>
typename _Unique_if<T>::_Single_object make_unique(Args&&... args) {return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
}std::remove_extent: 返回数组降低一个维度后的数据类型
template <class T>
typename _Unique_if<T>::_Unknown_bound make_unique(size_t n) {typedef typename std::remove_extent<T>::type U;return std::unique_ptr<T>(new U[n]());
}
lamda表达式
// cartographer/mapping/internal/collated_trajectory_builder.ccsensor_collator_->AddTrajectory(trajectory_id, expected_sensor_id_strings,[this](const std::string& sensor_id, std::unique_ptr<sensor::Data> data) {HandleCollatedSensorData(sensor_id, std::move(data));});// cartographer/sensor/collator_interface.h// Adds a trajectory to produce sorted sensor output for. Calls 'callback'// for each collated sensor data.virtual void AddTrajectory(int trajectory_id,const std::unordered_set<std::string>& expected_sensor_ids,const Callback& callback) = 0;// cartographer/sensor/internal/collator.ccvoid Collator::AddTrajectory(const int trajectory_id,const std::unordered_set<std::string>& expected_sensor_ids,const Callback& callback) {for (const auto& sensor_id : expected_sensor_ids) {const auto queue_key = QueueKey{trajectory_id, sensor_id};queue_.AddQueue(queue_key,[callback, sensor_id](std::unique_ptr<Data> data) {callback(sensor_id, std::move(data));});queue_keys_[trajectory_id].push_back(queue_key);}
}// cartographer/sensor/internal/ordered_multi_queue.ccvoid OrderedMultiQueue::AddQueue(const QueueKey& queue_key, Callback callback) {CHECK_EQ(queues_.count(queue_key), 0);queues_[queue_key].callback = std::move(callback);
}5 math.h
#include <cmath>
#include <vector>#include "Eigen/Core"
#include "cartographer/common/port.h"
#include "ceres/ceres.h"namespace cartographer {
namespace common {// Clamps 'value' to be in the range ['min', 'max'].
template <typename T>
T Clamp(const T value, const T min, const T max) {if (value > max) {return max;}if (value < min) {return min;}return value;
}// Calculates 'base'^'exponent'.
template <typename T>
constexpr T Power(T base, int exponent) {return (exponent != 0) ? base * Power(base, exponent - 1) : T(1);
}// Calculates a^2.
template <typename T>
constexpr T Pow2(T a) {return Power(a, 2);
}// Converts from degrees to radians.
constexpr double DegToRad(double deg) { return M_PI * deg / 180.; }// Converts form radians to degrees.
constexpr double RadToDeg(double rad) { return 180. * rad / M_PI; }// Bring the 'difference' between two angles into [-pi; pi].
template <typename T>
T NormalizeAngleDifference(T difference) {const T kPi = T(M_PI);while (difference > kPi) difference -= 2. * kPi;while (difference < -kPi) difference += 2. * kPi;return difference;
}template <typename T>
T atan2(const Eigen::Matrix<T, 2, 1>& vector) {return ceres::atan2(vector.y(), vector.x());
}template <typename T>
inline void QuaternionProduct(const double* const z, const T* const w,T* const zw) {zw[0] = z[0] * w[0] - z[1] * w[1] - z[2] * w[2] - z[3] * w[3];zw[1] = z[0] * w[1] + z[1] * w[0] + z[2] * w[3] - z[3] * w[2];zw[2] = z[0] * w[2] - z[1] * w[3] + z[2] * w[0] + z[3] * w[1];zw[3] = z[0] * w[3] + z[1] * w[2] - z[2] * w[1] + z[3] * w[0];
}} // namespace common
} // namespace cartographercartographer探秘第五章之 Cartographer 所用到的 C++11 新特性相关推荐
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