// -*- mode: c++ -*-
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#ifndef JSK_FOOTSTEP_PLANNER_FOOTSTEP_GRAPH_H_
#define JSK_FOOTSTEP_PLANNER_FOOTSTEP_GRAPH_H_
#include <ros/ros.h>
#include <jsk_footstep_msgs/FootstepArray.h>

#include "jsk_footstep_planner/graph.h"
#include "jsk_footstep_planner/footstep_state.h"
#include "jsk_footstep_planner/astar_solver.h"
#include "jsk_footstep_planner/ann_grid.h"
#include "jsk_footstep_planner/transition_limit.h"

namespace jsk_footstep_planner
{
  class FootstepGraph: public Graph<FootstepState>
  {
  public:
    typedef boost::shared_ptr<FootstepGraph> Ptr;
    FootstepGraph(const Eigen::Vector3f& resolution,
                  const bool use_pointcloud_model = false,
                  const bool lazy_projection = true,
                  const bool local_movement = false):
      max_successor_distance_(0.0), max_successor_rotation_(0.0),
      pos_goal_thr_(0.1), rot_goal_thr_(0.17), publish_progress_(false),
      resolution_(resolution),
      use_pointcloud_model_(use_pointcloud_model),
      lazy_projection_(lazy_projection),
      local_movement_(local_movement),
      pointcloud_model_2d_(new pcl::PointCloud<pcl::PointNormal>),
      tree_model_(new pcl::KdTreeFLANN<pcl::PointNormal>),
      tree_model_2d_(new pcl::search::Octree<pcl::PointNormal>(0.2)),
      grid_search_(new ANNGrid(0.05)),
      local_move_x_(0.1), local_move_y_(0.05), local_move_theta_(0.2),
      local_move_x_num_(3), local_move_y_num_(3), local_move_theta_num_(3),
      plane_estimation_max_iterations_(100),
      plane_estimation_min_inliers_(100),
      plane_estimation_outlier_threshold_(0.02),
      support_check_x_sampling_(3),
      support_check_y_sampling_(3),
      support_check_vertex_neighbor_threshold_(0.02),
      zero_state_(new FootstepState(0,
                                    Eigen::Affine3f::Identity(),
                                    Eigen::Vector3f::UnitX(),
                                    resolution_))
    {
    }
    virtual std::vector<StatePtr> successors(StatePtr target_state);
    virtual bool isGoal(StatePtr state);
    virtual void setBasicSuccessors(
      std::vector<Eigen::Affine3f> left_to_right_successors);
    
    virtual void setGoalState(
      FootstepState::Ptr left, FootstepState::Ptr right)
    {
      left_goal_state_ = left;
      right_goal_state_ = right;
    }

    virtual void setLeftGoalState(FootstepState::Ptr goal)
    {
      left_goal_state_ = goal;
    }
    
    virtual void setRightGoalState(FootstepState::Ptr goal)
    {
      right_goal_state_ = goal;
    }

    /**
     * @brief
     * return string about graph information.
     */
    virtual std::string infoString() const;
    
    virtual FootstepState::Ptr getGoal(int leg)
    {
      if (leg == jsk_footstep_msgs::Footstep::LEFT) {
        return left_goal_state_;
      }
      else if (leg == jsk_footstep_msgs::Footstep::RIGHT) {
        return right_goal_state_;
      }
      else {                    // TODO: error
        return goal_state_;
      }
    }

    virtual double maxSuccessorDistance()
    {
      return max_successor_distance_;
    }
    virtual double maxSuccessorRotation()
    {
      return max_successor_rotation_;
    }

    virtual void setProgressPublisher(ros::NodeHandle& nh, std::string topic)
    {
      publish_progress_ = true;
      pub_progress_ = nh.advertise<jsk_footstep_msgs::FootstepArray>(topic, 1);
    }

    virtual void setPointCloudModel(pcl::PointCloud<pcl::PointNormal>::Ptr model)
    {
      pointcloud_model_ = model;
      tree_model_->setInputCloud(pointcloud_model_);
      // Project point_cloud_model_
      pcl::ProjectInliers<pcl::PointNormal> proj;
      proj.setModelType(pcl::SACMODEL_PLANE);
      pcl::ModelCoefficients::Ptr
        plane_coefficients (new pcl::ModelCoefficients);
      plane_coefficients->values.resize(4.0);
      plane_coefficients->values[2] = 1.0; // TODO: configurable
      proj.setModelCoefficients(plane_coefficients);
      proj.setInputCloud(pointcloud_model_);
      proj.filter(*pointcloud_model_2d_);
      tree_model_2d_->setInputCloud(pointcloud_model_2d_);
      grid_search_->build(*model);
    }
    virtual bool projectGoal();
    virtual bool projectStart();
    
    virtual bool usePointCloudModel() const { return use_pointcloud_model_; }
    virtual bool lazyProjection()  const { return lazy_projection_; }
    virtual bool localMovement() const { return local_movement_; }
    virtual void setPositionGoalThreshold(double x) { pos_goal_thr_ = x; }
    virtual void setRotationGoalThreshold(double x) { rot_goal_thr_ = x; }
    virtual void setLocalXMovement(double x) { local_move_x_ = x; }
    virtual void setLocalYMovement(double x) { local_move_y_ = x; }
    virtual void setLocalThetaMovement(double x) { local_move_theta_ = x; }
    virtual void setLocalXMovementNum(size_t n) { local_move_x_num_ = n; }
    virtual void setLocalYMovementNum(size_t n) { local_move_y_num_ = n; }
    virtual void setLocalThetaMovementNum(size_t n) { local_move_theta_num_ = n; }
    virtual void setPlaneEstimationMaxIterations(int n) { plane_estimation_max_iterations_ = n; }
    virtual void setPlaneEstimationMinInliers(int n) { plane_estimation_min_inliers_ = n; }
    virtual void setPlaneEstimationOutlierThreshold(double d) { plane_estimation_outlier_threshold_ = d; }
    virtual void setSupportCheckXSampling(int n) { support_check_x_sampling_ = n; }
    virtual void setSupportCheckYSampling(int n) { support_check_y_sampling_ = n; }
    virtual void setSupportCheckVertexNeighborThreshold(double d) { support_check_vertex_neighbor_threshold_ = d; }
    virtual void setTransitionLimit(TransitionLimit::Ptr limit) { transition_limit_ = limit; }
    virtual TransitionLimit::Ptr getTransitionLimit() { return transition_limit_; }
    virtual void setGlobalTransitionLimit(TransitionLimit::Ptr limit) { global_transition_limit_ = limit; }
    virtual TransitionLimit::Ptr getGlobalTransitionLimit() { return global_transition_limit_; }
    virtual FootstepState::Ptr projectFootstep(FootstepState::Ptr in);
    virtual FootstepState::Ptr projectFootstep(FootstepState::Ptr in, unsigned int& state);

    virtual std::vector<FootstepState::Ptr> localMoveFootstepState(FootstepState::Ptr in);
  protected:
    pcl::PointCloud<pcl::PointNormal>::Ptr pointcloud_model_;
    pcl::PointCloud<pcl::PointNormal>::Ptr pointcloud_model_2d_;
    pcl::KdTreeFLANN<pcl::PointNormal>::Ptr tree_model_;
    //pcl::KdTreeFLANN<pcl::PointNormal>::Ptr tree_model_2d_;
    pcl::search::Octree<pcl::PointNormal>::Ptr tree_model_2d_;
    ANNGrid::Ptr grid_search_;
    std::vector<Eigen::Affine3f> successors_from_left_to_right_;
    std::vector<Eigen::Affine3f> successors_from_right_to_left_;
    FootstepState::Ptr left_goal_state_;
    FootstepState::Ptr right_goal_state_;
    /**
     * @brief
     * zero_state is used only for global transition limit
     */
    FootstepState::Ptr zero_state_;
    double max_successor_distance_;
    double max_successor_rotation_;
    double pos_goal_thr_;
    double rot_goal_thr_;
    bool publish_progress_;
    const bool use_pointcloud_model_;
    const bool lazy_projection_;
    const bool local_movement_;
    TransitionLimit::Ptr transition_limit_;
    TransitionLimit::Ptr global_transition_limit_;
    double local_move_x_;
    double local_move_y_;
    double local_move_theta_;
    size_t local_move_x_num_;
    size_t local_move_y_num_;
    size_t local_move_theta_num_;
    
    ros::Publisher pub_progress_;
    const Eigen::Vector3f resolution_;

    int plane_estimation_max_iterations_;
    int plane_estimation_min_inliers_;
    double plane_estimation_outlier_threshold_;
    int support_check_x_sampling_;
    int support_check_y_sampling_;
    double support_check_vertex_neighbor_threshold_;
  private:

  };

  // heuristic function
  double footstepHeuristicZero(
    SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph);
  double footstepHeuristicStraight(
    SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph);
  double footstepHeuristicStraightRotation(
    SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph);
  double footstepHeuristicStepCost(
    SolverNode<FootstepState, FootstepGraph>::Ptr node, FootstepGraph::Ptr graph,
    double first_rotation_weight,
    double second_rotation_weight);
}

#endif
