libpcl-dev 1.7.2-14build1 / usr / include / pcl-1.7 / pcl / registration / lum.h

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 * $Id: lum.h 5663 2012-05-02 13:49:39Z florentinus $
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#ifndef PCL_REGISTRATION_LUM_H_
#define PCL_REGISTRATION_LUM_H_

#include <pcl/pcl_base.h>
#include <pcl/registration/eigen.h>
#include <pcl/registration/boost.h>
#include <pcl/common/transforms.h>
#include <pcl/correspondence.h>
#include <pcl/registration/boost_graph.h>

namespace Eigen
{
  typedef Eigen::Matrix<float, 6, 1> Vector6f;
  typedef Eigen::Matrix<float, 6, 6> Matrix6f;
}

namespace pcl
{
  namespace registration
  {
    /** \brief Globally Consistent Scan Matching based on an algorithm by Lu and Milios.
      * \details A GraphSLAM algorithm where registration data is managed in a graph:
      * <ul>
      *  <li>Vertices represent poses and hold the point cloud data and relative transformations.</li>
      *  <li>Edges represent pose constraints and hold the correspondence data between two point clouds.</li>
      * </ul>
      * Computation uses the first point cloud in the SLAM graph as a reference pose and attempts to align all other point clouds to it simultaneously.
      * For more information:
      * <ul><li>
      * F. Lu, E. Milios,
      * Globally Consistent Range Scan Alignment for Environment Mapping,
      * Autonomous Robots 4, April 1997
      * </li><li>
      * Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg,
      * The Efficient Extension of Globally Consistent Scan Matching to 6 DoF,
      * In Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '08), June 2008
      * </li></ul>
      * Usage example:
      * \code
      * pcl::registration::LUM<pcl::PointXYZ> lum;
      * // Add point clouds as vertices to the SLAM graph
      * lum.addPointCloud (cloud_0);
      * lum.addPointCloud (cloud_1);
      * lum.addPointCloud (cloud_2);
      * // Use your favorite pairwise correspondence estimation algorithm(s)
      * corrs_0_to_1 = someAlgo (cloud_0, cloud_1);
      * corrs_1_to_2 = someAlgo (cloud_1, cloud_2);
      * corrs_2_to_0 = someAlgo (lum.getPointCloud (2), lum.getPointCloud (0));
      * // Add the correspondence results as edges to the SLAM graph
      * lum.setCorrespondences (0, 1, corrs_0_to_1);
      * lum.setCorrespondences (1, 2, corrs_1_to_2);
      * lum.setCorrespondences (2, 0, corrs_2_to_0);
      * // Change the computation parameters
      * lum.setMaxIterations (5);
      * lum.setConvergenceThreshold (0.0);
      * // Perform the actual LUM computation
      * lum.compute ();
      * // Return the concatenated point cloud result
      * cloud_out = lum.getConcatenatedCloud ();
      * // Return the separate point cloud transformations
      * for(int i = 0; i < lum.getNumVertices (); i++)
      * {
      *   transforms_out[i] = lum.getTransformation (i);
      * }
      * \endcode
      * \author Frits Florentinus, Jochen Sprickerhof
      * \ingroup registration
      */
    template<typename PointT>
    class LUM
    {
      public:
        typedef boost::shared_ptr<LUM<PointT> > Ptr;
        typedef boost::shared_ptr<const LUM<PointT> > ConstPtr;

        typedef pcl::PointCloud<PointT> PointCloud;
        typedef typename PointCloud::Ptr PointCloudPtr;
        typedef typename PointCloud::ConstPtr PointCloudConstPtr;

        struct VertexProperties
        {
          PointCloudPtr cloud_;
          Eigen::Vector6f pose_;
          EIGEN_MAKE_ALIGNED_OPERATOR_NEW
        };
        struct EdgeProperties
        {
          pcl::CorrespondencesPtr corrs_;
          Eigen::Matrix6f cinv_;
          Eigen::Vector6f cinvd_;
          EIGEN_MAKE_ALIGNED_OPERATOR_NEW
        };

        typedef boost::adjacency_list<boost::eigen_vecS, boost::eigen_vecS, boost::bidirectionalS, VertexProperties, EdgeProperties, boost::no_property, boost::eigen_listS> SLAMGraph;
        typedef boost::shared_ptr<SLAMGraph> SLAMGraphPtr;
        typedef typename SLAMGraph::vertex_descriptor Vertex;
        typedef typename SLAMGraph::edge_descriptor Edge;

        /** \brief Empty constructor.
          */
        LUM () 
          : slam_graph_ (new SLAMGraph)
          , max_iterations_ (5)
          , convergence_threshold_ (0.0)
        {
        }

        /** \brief Set the internal SLAM graph structure.
          * \details All data used and produced by LUM is stored in this boost::adjacency_list.
          * It is recommended to use the LUM class itself to build the graph.
          * This method could otherwise be useful for managing several SLAM graphs in one instance of LUM.
          * \param[in] slam_graph The new SLAM graph.
          */
        inline void
        setLoopGraph (const SLAMGraphPtr &slam_graph);

        /** \brief Get the internal SLAM graph structure.
          * \details All data used and produced by LUM is stored in this boost::adjacency_list.
          * It is recommended to use the LUM class itself to build the graph.
          * This method could otherwise be useful for managing several SLAM graphs in one instance of LUM.
          * \return The current SLAM graph.
          */
        inline SLAMGraphPtr
        getLoopGraph () const;

        /** \brief Get the number of vertices in the SLAM graph.
          * \return The current number of vertices in the SLAM graph.
          */
        typename SLAMGraph::vertices_size_type
        getNumVertices () const;

        /** \brief Set the maximum number of iterations for the compute() method.
          * \details The compute() method finishes when max_iterations are met or when the convergence criteria is met.
          * \param[in] max_iterations The new maximum number of iterations (default = 5).
          */
        void
        setMaxIterations (int max_iterations);

        /** \brief Get the maximum number of iterations for the compute() method.
          * \details The compute() method finishes when max_iterations are met or when the convergence criteria is met.
          * \return The current maximum number of iterations (default = 5).
          */
        inline int
        getMaxIterations () const;

        /** \brief Set the convergence threshold for the compute() method.
          * \details When the compute() method computes the new poses relative to the old poses, it will determine the length of the difference vector.
          * When the average length of all difference vectors becomes less than the convergence_threshold the convergence is assumed to be met.
          * \param[in] convergence_threshold The new convergence threshold (default = 0.0).
          */
        void
        setConvergenceThreshold (float convergence_threshold);

        /** \brief Get the convergence threshold for the compute() method.
          * \details When the compute() method computes the new poses relative to the old poses, it will determine the length of the difference vector.
          * When the average length of all difference vectors becomes less than the convergence_threshold the convergence is assumed to be met.
          * \return The current convergence threshold (default = 0.0).
          */
        inline float
        getConvergenceThreshold () const;

        /** \brief Add a new point cloud to the SLAM graph.
          * \details This method will add a new vertex to the SLAM graph and attach a point cloud to that vertex.
          * Optionally you can specify a pose estimate for this point cloud.
          * A vertex' pose is always relative to the first vertex in the SLAM graph, i.e. the first point cloud that was added.
          * Because this first vertex is the reference, you can not set a pose estimate for this vertex.
          * Providing pose estimates to the vertices in the SLAM graph will reduce overall computation time of LUM.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] cloud The new point cloud.
          * \param[in] pose (optional) The pose estimate relative to the reference pose (first point cloud that was added).
          * \return The vertex descriptor of the newly created vertex.
          */
        Vertex
        addPointCloud (const PointCloudPtr &cloud, const Eigen::Vector6f &pose = Eigen::Vector6f::Zero ());

        /** \brief Change a point cloud on one of the SLAM graph's vertices.
          * \details This method will change the point cloud attached to an existing vertex and will not alter the SLAM graph structure.
          * Note that the correspondences attached to this vertex will not change and may need to be updated manually.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to change the point cloud.
          * \param[in] cloud The new point cloud for that vertex.
          */
        inline void
        setPointCloud (const Vertex &vertex, const PointCloudPtr &cloud);

        /** \brief Return a point cloud from one of the SLAM graph's vertices.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to return the point cloud.
          * \return The current point cloud for that vertex.
          */
        inline PointCloudPtr
        getPointCloud (const Vertex &vertex) const;

        /** \brief Change a pose estimate on one of the SLAM graph's vertices.
          * \details A vertex' pose is always relative to the first vertex in the SLAM graph, i.e. the first point cloud that was added.
          * Because this first vertex is the reference, you can not set a pose estimate for this vertex.
          * Providing pose estimates to the vertices in the SLAM graph will reduce overall computation time of LUM.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to set the pose estimate.
          * \param[in] pose The new pose estimate for that vertex.
          */
        inline void
        setPose (const Vertex &vertex, const Eigen::Vector6f &pose);

        /** \brief Return a pose estimate from one of the SLAM graph's vertices.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to return the pose estimate.
          * \return The current pose estimate of that vertex.
          */
        inline Eigen::Vector6f
        getPose (const Vertex &vertex) const;

        /** \brief Return a pose estimate from one of the SLAM graph's vertices as an affine transformation matrix.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to return the transformation matrix.
          * \return The current transformation matrix of that vertex.
          */
        inline Eigen::Affine3f
        getTransformation (const Vertex &vertex) const;

        /** \brief Add/change a set of correspondences for one of the SLAM graph's edges.
          * \details The edges in the SLAM graph are directional and point from source vertex to target vertex.
          * The query indices of the correspondences, index the points at the source vertex' point cloud.
          * The matching indices of the correspondences, index the points at the target vertex' point cloud.
          * If no edge was present at the specified location, this method will add a new edge to the SLAM graph and attach the correspondences to that edge.
          * If the edge was already present, this method will overwrite the correspondence information of that edge and will not alter the SLAM graph structure.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] source_vertex The vertex descriptor of the correspondences' source point cloud.
          * \param[in] target_vertex The vertex descriptor of the correspondences' target point cloud.
          * \param[in] corrs The new set of correspondences for that edge.
          */
        void
        setCorrespondences (const Vertex &source_vertex, 
                            const Vertex &target_vertex, 
                            const pcl::CorrespondencesPtr &corrs);

        /** \brief Return a set of correspondences from one of the SLAM graph's edges.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] source_vertex The vertex descriptor of the correspondences' source point cloud.
          * \param[in] target_vertex The vertex descriptor of the correspondences' target point cloud.
          * \return The current set of correspondences of that edge.
          */
        inline pcl::CorrespondencesPtr
        getCorrespondences (const Vertex &source_vertex, const Vertex &target_vertex) const;

        /** \brief Perform LUM's globally consistent scan matching.
          * \details Computation uses the first point cloud in the SLAM graph as a reference pose and attempts to align all other point clouds to it simultaneously.
          * <br>
          * Things to keep in mind:
          * <ul>
          *  <li>Only those parts of the graph connected to the reference pose will properly align to it.</li>
          *  <li>All sets of correspondences should span the same space and need to be sufficient to determine a rigid transformation.</li>
          *  <li>The algorithm draws it strength from loops in the graph because it will distribute errors evenly amongst those loops.</li>
          * </ul>
          * Computation ends when either of the following conditions hold:
          * <ul>
          *  <li>The number of iterations reaches max_iterations. Use setMaxIterations() to change.</li>
          *  <li>The convergence criteria is met. Use setConvergenceThreshold() to change.</li>
          * </ul>
          * Computation will change the pose estimates for the vertices of the SLAM graph, not the point clouds attached to them.
          * The results can be retrieved with getPose(), getTransformation(), getTransformedCloud() or getConcatenatedCloud().
          */
        void
        compute ();

        /** \brief Return a point cloud from one of the SLAM graph's vertices compounded onto its current pose estimate.
          * \note Vertex descriptors are typecastable to int.
          * \param[in] vertex The vertex descriptor of which to return the transformed point cloud.
          * \return The transformed point cloud of that vertex.
          */
        PointCloudPtr
        getTransformedCloud (const Vertex &vertex) const;

        /** \brief Return a concatenated point cloud of all the SLAM graph's point clouds compounded onto their current pose estimates.
          * \return The concatenated transformed point clouds of the entire SLAM graph.
          */
        PointCloudPtr
        getConcatenatedCloud () const;

      protected:
        /** \brief Linearized computation of C^-1 and C^-1*D (results stored in slam_graph_). */
        void
        computeEdge (const Edge &e);

        /** \brief Returns a pose corrected 6DoF incidence matrix. */
        inline Eigen::Matrix6f
        incidenceCorrection (const Eigen::Vector6f &pose);

      private:
        /** \brief The internal SLAM graph structure. */
        SLAMGraphPtr slam_graph_;

        /** \brief The maximum number of iterations for the compute() method. */
        int max_iterations_;

        /** \brief The convergence threshold for the summed vector lengths of all poses. */
        float convergence_threshold_;
    };
  }
}

#ifdef PCL_NO_PRECOMPILE
#include <pcl/registration/impl/lum.hpp>
#endif

#endif  // PCL_REGISTRATION_LUM_H_