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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2016 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
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// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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//
// Author: vitus@google.com (Michael Vitus)
//
// An example of solving a graph-based formulation of Simultaneous Localization
// and Mapping (SLAM). It reads a 2D pose graph problem definition file in the
// g2o format, formulates and solves the Ceres optimization problem, and outputs
// the original and optimized poses to file for plotting.
#include <fstream>
#include <iostream>
#include <map>
#include <string>
#include <vector>
#include "angle_manifold.h"
#include "ceres/ceres.h"
#include "common/read_g2o.h"
#include "gflags/gflags.h"
#include "glog/logging.h"
#include "pose_graph_2d_error_term.h"
#include "types.h"
DEFINE_string(input, "", "The pose graph definition filename in g2o format.");
namespace ceres {
namespace examples {
namespace {
// Constructs the nonlinear least squares optimization problem from the pose
// graph constraints.
void BuildOptimizationProblem(const std::vector<Constraint2d>& constraints,
std::map<int, Pose2d>* poses,
ceres::Problem* problem) {
CHECK(poses != nullptr);
CHECK(problem != nullptr);
if (constraints.empty()) {
LOG(INFO) << "No constraints, no problem to optimize.";
return;
}
ceres::LossFunction* loss_function = nullptr;
ceres::Manifold* angle_manifold = AngleManifold::Create();
for (std::vector<Constraint2d>::const_iterator constraints_iter =
constraints.begin();
constraints_iter != constraints.end();
++constraints_iter) {
const Constraint2d& constraint = *constraints_iter;
std::map<int, Pose2d>::iterator pose_begin_iter =
poses->find(constraint.id_begin);
CHECK(pose_begin_iter != poses->end())
<< "Pose with ID: " << constraint.id_begin << " not found.";
std::map<int, Pose2d>::iterator pose_end_iter =
poses->find(constraint.id_end);
CHECK(pose_end_iter != poses->end())
<< "Pose with ID: " << constraint.id_end << " not found.";
const Eigen::Matrix3d sqrt_information =
constraint.information.llt().matrixL();
// Ceres will take ownership of the pointer.
ceres::CostFunction* cost_function = PoseGraph2dErrorTerm::Create(
constraint.x, constraint.y, constraint.yaw_radians, sqrt_information);
problem->AddResidualBlock(cost_function,
loss_function,
&pose_begin_iter->second.x,
&pose_begin_iter->second.y,
&pose_begin_iter->second.yaw_radians,
&pose_end_iter->second.x,
&pose_end_iter->second.y,
&pose_end_iter->second.yaw_radians);
problem->SetManifold(&pose_begin_iter->second.yaw_radians, angle_manifold);
problem->SetManifold(&pose_end_iter->second.yaw_radians, angle_manifold);
}
// The pose graph optimization problem has three DOFs that are not fully
// constrained. This is typically referred to as gauge freedom. You can apply
// a rigid body transformation to all the nodes and the optimization problem
// will still have the exact same cost. The Levenberg-Marquardt algorithm has
// internal damping which mitigate this issue, but it is better to properly
// constrain the gauge freedom. This can be done by setting one of the poses
// as constant so the optimizer cannot change it.
std::map<int, Pose2d>::iterator pose_start_iter = poses->begin();
CHECK(pose_start_iter != poses->end()) << "There are no poses.";
problem->SetParameterBlockConstant(&pose_start_iter->second.x);
problem->SetParameterBlockConstant(&pose_start_iter->second.y);
problem->SetParameterBlockConstant(&pose_start_iter->second.yaw_radians);
}
// Returns true if the solve was successful.
bool SolveOptimizationProblem(ceres::Problem* problem) {
CHECK(problem != nullptr);
ceres::Solver::Options options;
options.max_num_iterations = 100;
options.linear_solver_type = ceres::SPARSE_NORMAL_CHOLESKY;
ceres::Solver::Summary summary;
ceres::Solve(options, problem, &summary);
std::cout << summary.FullReport() << '\n';
return summary.IsSolutionUsable();
}
// Output the poses to the file with format: ID x y yaw_radians.
bool OutputPoses(const std::string& filename,
const std::map<int, Pose2d>& poses) {
std::fstream outfile;
outfile.open(filename.c_str(), std::istream::out);
if (!outfile) {
std::cerr << "Error opening the file: " << filename << '\n';
return false;
}
for (std::map<int, Pose2d>::const_iterator poses_iter = poses.begin();
poses_iter != poses.end();
++poses_iter) {
const std::map<int, Pose2d>::value_type& pair = *poses_iter;
outfile << pair.first << " " << pair.second.x << " " << pair.second.y << ' '
<< pair.second.yaw_radians << '\n';
}
return true;
}
} // namespace
} // namespace examples
} // namespace ceres
int main(int argc, char** argv) {
google::InitGoogleLogging(argv[0]);
GFLAGS_NAMESPACE::ParseCommandLineFlags(&argc, &argv, true);
CHECK(FLAGS_input != "") << "Need to specify the filename to read.";
std::map<int, ceres::examples::Pose2d> poses;
std::vector<ceres::examples::Constraint2d> constraints;
CHECK(ceres::examples::ReadG2oFile(FLAGS_input, &poses, &constraints))
<< "Error reading the file: " << FLAGS_input;
std::cout << "Number of poses: " << poses.size() << '\n';
std::cout << "Number of constraints: " << constraints.size() << '\n';
CHECK(ceres::examples::OutputPoses("poses_original.txt", poses))
<< "Error outputting to poses_original.txt";
ceres::Problem problem;
ceres::examples::BuildOptimizationProblem(constraints, &poses, &problem);
CHECK(ceres::examples::SolveOptimizationProblem(&problem))
<< "The solve was not successful, exiting.";
CHECK(ceres::examples::OutputPoses("poses_optimized.txt", poses))
<< "Error outputting to poses_original.txt";
return 0;
}