model_based_planning_context.cpp

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/* Author: Ioan Sucan */

#include <moveit/ompl_interface/model_based_planning_context.h>
#include <moveit/ompl_interface/detail/state_validity_checker.h>
#include <moveit/ompl_interface/detail/constrained_sampler.h>
#include <moveit/ompl_interface/detail/constrained_goal_sampler.h>
#include <moveit/ompl_interface/detail/goal_union.h>
#include <moveit/ompl_interface/detail/projection_evaluators.h>
#include <moveit/ompl_interface/constraints_library.h>
#include <moveit/kinematic_constraints/utils.h>
#include <moveit/profiler/profiler.h>
#include <eigen_conversions/eigen_msg.h>

#include <ompl/base/samplers/UniformValidStateSampler.h>
#include <ompl/base/goals/GoalLazySamples.h>
#include <ompl/tools/config/SelfConfig.h>
#include <ompl/base/spaces/SE3StateSpace.h>
#include <ompl/datastructures/PDF.h>

ompl_interface::ModelBasedPlanningContext::ModelBasedPlanningContext(const std::string &name, const ModelBasedPlanningContextSpecification &spec) :
  planning_interface::PlanningContext(name, spec.state_space_->getJointModelGroup()->getName()),
  spec_(spec),
  complete_initial_robot_state_(spec.state_space_->getRobotModel()),
  ompl_simple_setup_(spec.state_space_),
  ompl_benchmark_(ompl_simple_setup_),
  ompl_parallel_plan_(ompl_simple_setup_.getProblemDefinition()),
  last_plan_time_(0.0),
  last_simplify_time_(0.0),
  max_goal_samples_(0),
  max_state_sampling_attempts_(0),
  max_goal_sampling_attempts_(0),
  max_planning_threads_(0),
  max_solution_segment_length_(0.0),
  minimum_waypoint_count_(0),
  use_state_validity_cache_(true),
  simplify_solutions_(true)
{
  ompl_simple_setup_.getStateSpace()->computeSignature(space_signature_);
  ompl_simple_setup_.getStateSpace()->setStateSamplerAllocator(boost::bind(&ModelBasedPlanningContext::allocPathConstrainedSampler, this, _1));
}

void ompl_interface::ModelBasedPlanningContext::setProjectionEvaluator(const std::string &peval)
{
  if (!spec_.state_space_)
  {
    logError("No state space is configured yet");
    return;
  }
  ob::ProjectionEvaluatorPtr pe = getProjectionEvaluator(peval);
  if (pe)
    spec_.state_space_->registerDefaultProjection(pe);
}

ompl::base::ProjectionEvaluatorPtr ompl_interface::ModelBasedPlanningContext::getProjectionEvaluator(const std::string &peval) const
{
  if (peval.find_first_of("link(") == 0 && peval[peval.length() - 1] == ')')
  {
    std::string link_name = peval.substr(5, peval.length() - 6);
    if (getRobotModel()->hasLinkModel(link_name))
      return ob::ProjectionEvaluatorPtr(new ProjectionEvaluatorLinkPose(this, link_name));
    else
      logError("Attempted to set projection evaluator with respect to position of link '%s', but that link is not known to the kinematic model.", link_name.c_str());
  }
  else
    if (peval.find_first_of("joints(") == 0 && peval[peval.length() - 1] == ')')
    {
      std::string joints = peval.substr(7, peval.length() - 8);
      boost::replace_all(joints, ",", " ");
      std::vector<std::pair<std::string, unsigned int> > j;
      std::stringstream ss(joints);
      while (ss.good() && !ss.eof())
      {
    std::string v; ss >> v >> std::ws;
    if (getJointModelGroup()->hasJointModel(v))
    {
      unsigned int vc = getJointModelGroup()->getJointModel(v)->getVariableCount();
      if (vc > 0)
        j.push_back(std::make_pair(v, vc));
      else
        logWarn("%s: Ignoring joint '%s' in projection since it has 0 DOF", name_.c_str(), v.c_str());
    }
    else
      logError("%s: Attempted to set projection evaluator with respect to value of joint '%s', but that joint is not known to the group '%s'.",
                   name_.c_str(), v.c_str(), getGroupName().c_str());
      }
      if (j.empty())
    logError("%s: No valid joints specified for joint projection", name_.c_str());
      else
    return ob::ProjectionEvaluatorPtr(new ProjectionEvaluatorJointValue(this, j));
    }
    else
      logError("Unable to allocate projection evaluator based on description: '%s'", peval.c_str());
  return ob::ProjectionEvaluatorPtr();
}

ompl::base::StateSamplerPtr ompl_interface::ModelBasedPlanningContext::allocPathConstrainedSampler(const ompl::base::StateSpace *ss) const
{
  if (spec_.state_space_.get() != ss)
  {
    logError("%s: Attempted to allocate a state sampler for an unknown state space", name_.c_str());
    return ompl::base::StateSamplerPtr();
  }

  logDebug("%s: Allocating a new state sampler (attempts to use path constraints)", name_.c_str());

  if (path_constraints_)
  {
    if (spec_.constraints_library_)
    {
      const ConstraintApproximationPtr &ca = spec_.constraints_library_->getConstraintApproximation(path_constraints_msg_);
      if (ca)
      {
        ompl::base::StateSamplerAllocator c_ssa = ca->getStateSamplerAllocator(path_constraints_msg_);
        if (c_ssa)
        {
          ompl::base::StateSamplerPtr res = c_ssa(ss);
          if (res)
          {
            logInform("%s: Using precomputed state sampler (approximated constraint space) for constraint '%s'", name_.c_str(), path_constraints_msg_.name.c_str());
            return res;
          }
        }
      }
    }

    constraint_samplers::ConstraintSamplerPtr cs;
    if (spec_.constraint_sampler_manager_)
      cs = spec_.constraint_sampler_manager_->selectSampler(getPlanningScene(), getGroupName(), path_constraints_->getAllConstraints());

    if (cs)
    {
      logInform("%s: Allocating specialized state sampler for state space", name_.c_str());
      return ob::StateSamplerPtr(new ConstrainedSampler(this, cs));
    }
  }
  logDebug("%s: Allocating default state sampler for state space", name_.c_str());
  return ss->allocDefaultStateSampler();
}

void ompl_interface::ModelBasedPlanningContext::configure()
{
  // convert the input state to the corresponding OMPL state
  ompl::base::ScopedState<> ompl_start_state(spec_.state_space_);
  spec_.state_space_->copyToOMPLState(ompl_start_state.get(), getCompleteInitialRobotState());
  ompl_simple_setup_.setStartState(ompl_start_state);
  ompl_simple_setup_.setStateValidityChecker(ob::StateValidityCheckerPtr(new StateValidityChecker(this)));

  if (path_constraints_ && spec_.constraints_library_)
  {
    const ConstraintApproximationPtr &ca = spec_.constraints_library_->getConstraintApproximation(path_constraints_msg_);
    if (ca)
    {
      getOMPLStateSpace()->setInterpolationFunction(ca->getInterpolationFunction());
      logInform("Using precomputed interpolation states");
    }
  }

  useConfig();
  if (ompl_simple_setup_.getGoal())
    ompl_simple_setup_.setup();
}

void ompl_interface::ModelBasedPlanningContext::useConfig()
{
  const std::map<std::string, std::string> &config = spec_.config_;
  if (config.empty())
    return;
  std::map<std::string, std::string> cfg = config;

  // set the projection evaluator
  std::map<std::string, std::string>::iterator it = cfg.find("projection_evaluator");
  if (it != cfg.end())
  {
    setProjectionEvaluator(boost::trim_copy(it->second));
    cfg.erase(it);
  }

  if (cfg.empty())
    return;

  // remove the 'type' parameter; the rest are parameters for the planner itself
  it = cfg.find("type");
  if (it == cfg.end())
  {
    if (name_ != getGroupName())
      logWarn("%s: Attribute 'type' not specified in planner configuration", name_.c_str());
  }
  else
  {
    std::string type = it->second;
    cfg.erase(it);
    ompl_simple_setup_.setPlannerAllocator(boost::bind(spec_.planner_selector_(type), _1,
                               name_ != getGroupName() ? name_ : "", spec_));
    logInform("Planner configuration '%s' will use planner '%s'. Additional configuration parameters will be set when the planner is constructed.",
              name_.c_str(), type.c_str());
  }

  // call the setParams() after setup(), so we know what the params are
  ompl_simple_setup_.getSpaceInformation()->setup();
  ompl_simple_setup_.getSpaceInformation()->params().setParams(cfg, true);
  // call setup() again for possibly new param values
  ompl_simple_setup_.getSpaceInformation()->setup();
}

void ompl_interface::ModelBasedPlanningContext::setPlanningVolume(const moveit_msgs::WorkspaceParameters &wparams)
{
  if (wparams.min_corner.x == wparams.max_corner.x && wparams.min_corner.x == 0.0 &&
      wparams.min_corner.y == wparams.max_corner.y && wparams.min_corner.y == 0.0 &&
      wparams.min_corner.z == wparams.max_corner.z && wparams.min_corner.z == 0.0)
    logWarn("It looks like the planning volume was not specified.");

  logDebug("%s: Setting planning volume (affects SE2 & SE3 joints only) to x = [%f, %f], y = [%f, %f], z = [%f, %f]", name_.c_str(),
           wparams.min_corner.x, wparams.max_corner.x, wparams.min_corner.y, wparams.max_corner.y, wparams.min_corner.z, wparams.max_corner.z);

  spec_.state_space_->setPlanningVolume(wparams.min_corner.x, wparams.max_corner.x,
                                        wparams.min_corner.y, wparams.max_corner.y,
                                        wparams.min_corner.z, wparams.max_corner.z);
}

void ompl_interface::ModelBasedPlanningContext::simplifySolution(double timeout)
{
  ompl_simple_setup_.simplifySolution(timeout);
  last_simplify_time_ = ompl_simple_setup_.getLastSimplificationTime();
}

void ompl_interface::ModelBasedPlanningContext::interpolateSolution()
{
  if (ompl_simple_setup_.haveSolutionPath())
  {
    og::PathGeometric &pg = ompl_simple_setup_.getSolutionPath();
    pg.interpolate(std::max((unsigned int)floor(0.5 + pg.length() / max_solution_segment_length_), minimum_waypoint_count_));
  }
}

void ompl_interface::ModelBasedPlanningContext::convertPath(const ompl::geometric::PathGeometric &pg, robot_trajectory::RobotTrajectory &traj) const
{
  robot_state::RobotState ks = complete_initial_robot_state_;
  for (std::size_t i = 0 ; i < pg.getStateCount() ; ++i)
  {
    spec_.state_space_->copyToRobotState(ks, pg.getState(i));
    traj.addSuffixWayPoint(ks, 0.0);
  }
}

bool ompl_interface::ModelBasedPlanningContext::getSolutionPath(robot_trajectory::RobotTrajectory &traj) const
{
  traj.clear();
  if (!ompl_simple_setup_.haveSolutionPath())
    return false;
  convertPath(ompl_simple_setup_.getSolutionPath(), traj);
  return true;
}

void ompl_interface::ModelBasedPlanningContext::setVerboseStateValidityChecks(bool flag)
{
  if (ompl_simple_setup_.getStateValidityChecker())
    static_cast<StateValidityChecker*>(ompl_simple_setup_.getStateValidityChecker().get())->setVerbose(flag);
}

ompl::base::GoalPtr ompl_interface::ModelBasedPlanningContext::constructGoal()
{
  // ******************* set up the goal representation, based on goal constraints

  std::vector<ob::GoalPtr> goals;
  for (std::size_t i = 0 ; i < goal_constraints_.size() ; ++i)
  {
    constraint_samplers::ConstraintSamplerPtr cs;
    if (spec_.constraint_sampler_manager_)
      cs = spec_.constraint_sampler_manager_->selectSampler(getPlanningScene(), getGroupName(), goal_constraints_[i]->getAllConstraints());
    if (cs)
    {
      ob::GoalPtr g = ob::GoalPtr(new ConstrainedGoalSampler(this, goal_constraints_[i], cs));
      goals.push_back(g);
    }
  }

  if (!goals.empty())
    return goals.size() == 1 ? goals[0] : ompl::base::GoalPtr(new GoalSampleableRegionMux(goals));
  else
    logError("Unable to construct goal representation");

  return ob::GoalPtr();
}

void ompl_interface::ModelBasedPlanningContext::setCompleteInitialState(const robot_state::RobotState &complete_initial_robot_state)
{
  complete_initial_robot_state_ = complete_initial_robot_state;
}

void ompl_interface::ModelBasedPlanningContext::clear()
{
  ompl_simple_setup_.clear();
  ompl_simple_setup_.clearStartStates();
  ompl_simple_setup_.setGoal(ob::GoalPtr());
  ompl_simple_setup_.setStateValidityChecker(ob::StateValidityCheckerPtr());
  path_constraints_.reset();
  goal_constraints_.clear();
  getOMPLStateSpace()->setInterpolationFunction(InterpolationFunction());
}

bool ompl_interface::ModelBasedPlanningContext::setPathConstraints(const moveit_msgs::Constraints &path_constraints,
                                   moveit_msgs::MoveItErrorCodes *error)
{
  // ******************* set the path constraints to use
  path_constraints_.reset(new kinematic_constraints::KinematicConstraintSet(getRobotModel()));
  path_constraints_->add(path_constraints, getPlanningScene()->getTransforms());
  path_constraints_msg_ = path_constraints;

  return true;
}

bool ompl_interface::ModelBasedPlanningContext::setGoalConstraints(const std::vector<moveit_msgs::Constraints> &goal_constraints,
                                   const moveit_msgs::Constraints &path_constraints,
                                   moveit_msgs::MoveItErrorCodes *error)
{

  // ******************* check if the input is correct
  goal_constraints_.clear();
  for (std::size_t i = 0 ; i < goal_constraints.size() ; ++i)
  {
    moveit_msgs::Constraints constr = kinematic_constraints::mergeConstraints(goal_constraints[i], path_constraints);
    kinematic_constraints::KinematicConstraintSetPtr kset(new kinematic_constraints::KinematicConstraintSet(getRobotModel()));
    kset->add(constr, getPlanningScene()->getTransforms());
    if (!kset->empty())
      goal_constraints_.push_back(kset);
  }

  if (goal_constraints_.empty())
  {
    logWarn("%s: No goal constraints specified. There is no problem to solve.", name_.c_str());
    if (error)
      error->val = moveit_msgs::MoveItErrorCodes::INVALID_GOAL_CONSTRAINTS;
    return false;
  }

  ob::GoalPtr goal = constructGoal();
  ompl_simple_setup_.setGoal(goal);
  if (goal)
    return true;
  else
    return false;
}

bool ompl_interface::ModelBasedPlanningContext::benchmark(double timeout, unsigned int count, const std::string &filename)
{
  ompl_benchmark_.clearPlanners();
  ompl_simple_setup_.setup();
  ompl_benchmark_.addPlanner(ompl_simple_setup_.getPlanner());
  ompl_benchmark_.setExperimentName(getRobotModel()->getName() + "_" + getGroupName() + "_" +
                    getPlanningScene()->getName() + "_" + name_);

  ot::Benchmark::Request req;
  req.maxTime = timeout;
  req.runCount = count;
  req.displayProgress = true;
  req.saveConsoleOutput = false;
  ompl_benchmark_.benchmark(req);
  return filename.empty() ? ompl_benchmark_.saveResultsToFile() : ompl_benchmark_.saveResultsToFile(filename.c_str());
}

void ompl_interface::ModelBasedPlanningContext::preSolve()
{
  // clear previously computed solutions
  ompl_simple_setup_.getProblemDefinition()->clearSolutionPaths();
  const ob::PlannerPtr planner = ompl_simple_setup_.getPlanner();
  if (planner)
    planner->clear();
  bool gls = ompl_simple_setup_.getGoal()->hasType(ob::GOAL_LAZY_SAMPLES);
  // just in case sampling is not started
  if (gls)
    static_cast<ob::GoalLazySamples*>(ompl_simple_setup_.getGoal().get())->startSampling();

  ompl_simple_setup_.getSpaceInformation()->getMotionValidator()->resetMotionCounter();
}

void ompl_interface::ModelBasedPlanningContext::postSolve()
{
  bool gls = ompl_simple_setup_.getGoal()->hasType(ob::GOAL_LAZY_SAMPLES);
  if (gls)
    // just in case we need to stop sampling
    static_cast<ob::GoalLazySamples*>(ompl_simple_setup_.getGoal().get())->stopSampling();

  int v = ompl_simple_setup_.getSpaceInformation()->getMotionValidator()->getValidMotionCount();
  int iv = ompl_simple_setup_.getSpaceInformation()->getMotionValidator()->getInvalidMotionCount();
  logDebug("There were %d valid motions and %d invalid motions.", v, iv);

  if (ompl_simple_setup_.getProblemDefinition()->hasApproximateSolution())
    logWarn("Computed solution is approximate");
}

bool ompl_interface::ModelBasedPlanningContext::solve(planning_interface::MotionPlanResponse &res)
{
  if (solve(request_.allowed_planning_time, request_.num_planning_attempts))
  {
    double ptime = getLastPlanTime();
    if (simplify_solutions_ && ptime < request_.allowed_planning_time)
    {
      simplifySolution(request_.allowed_planning_time - ptime);
      ptime += getLastSimplifyTime();
    }
    interpolateSolution();

    // fill the response
    logDebug("%s: Returning successful solution with %lu states", getName().c_str(),
             getOMPLSimpleSetup().getSolutionPath().getStateCount());

    res.trajectory_.reset(new robot_trajectory::RobotTrajectory(getRobotModel(), getGroupName()));
    getSolutionPath(*res.trajectory_);
    res.planning_time_ = ptime;
    return true;
  }
  else
  {
    logInform("Unable to solve the planning problem");
    res.error_code_.val = moveit_msgs::MoveItErrorCodes::PLANNING_FAILED;
    return false;
  }
}

bool ompl_interface::ModelBasedPlanningContext::solve(planning_interface::MotionPlanDetailedResponse &res)
{
  if (solve(request_.allowed_planning_time, request_.num_planning_attempts))
  {
    res.trajectory_.reserve(3);

    // add info about planned solution
    double ptime = getLastPlanTime();
    res.processing_time_.push_back(ptime);
    res.description_.push_back("plan");
    res.trajectory_.resize(res.trajectory_.size() + 1);
    res.trajectory_.back().reset(new robot_trajectory::RobotTrajectory(getRobotModel(), getGroupName()));
    getSolutionPath(*res.trajectory_.back());

    // simplify solution if time remains
    if (simplify_solutions_ && ptime < request_.allowed_planning_time)
    {
      simplifySolution(request_.allowed_planning_time - ptime);
      res.processing_time_.push_back(getLastSimplifyTime());
      res.description_.push_back("simplify");
      res.trajectory_.resize(res.trajectory_.size() + 1);
      res.trajectory_.back().reset(new robot_trajectory::RobotTrajectory(getRobotModel(), getGroupName()));
      getSolutionPath(*res.trajectory_.back());
    }

    ompl::time::point start_interpolate = ompl::time::now();
    interpolateSolution();
    res.processing_time_.push_back(ompl::time::seconds(ompl::time::now() - start_interpolate));
    res.description_.push_back("interpolate");
    res.trajectory_.resize(res.trajectory_.size() + 1);
    res.trajectory_.back().reset(new robot_trajectory::RobotTrajectory(getRobotModel(), getGroupName()));
    getSolutionPath(*res.trajectory_.back());

    // fill the response
    logDebug("%s: Returning successful solution with %lu states", getName().c_str(),
             getOMPLSimpleSetup().getSolutionPath().getStateCount());
    return true;
  }
  else
  {
    logInform("Unable to solve the planning problem");
    res.error_code_.val = moveit_msgs::MoveItErrorCodes::PLANNING_FAILED;
    return false;
  }
}

bool ompl_interface::ModelBasedPlanningContext::solve(double timeout, unsigned int count)
{
  moveit::Profiler::ScopedBlock sblock("PlanningContext:Solve");
  ompl::time::point start = ompl::time::now();
  preSolve();

  bool result = false;
  if (count <= 1)
  {
    logDebug("%s: Solving the planning problem once...", name_.c_str());
    ob::PlannerTerminationCondition ptc = ob::timedPlannerTerminationCondition(timeout - ompl::time::seconds(ompl::time::now() - start));
    registerTerminationCondition(ptc);
    result = ompl_simple_setup_.solve(ptc) == ompl::base::PlannerStatus::EXACT_SOLUTION;
    last_plan_time_ = ompl_simple_setup_.getLastPlanComputationTime();
    unregisterTerminationCondition();
  }
  else
  {
    logDebug("%s: Solving the planning problem %u times...", name_.c_str(), count);
    ompl_parallel_plan_.clearHybridizationPaths();
    if (count <= max_planning_threads_)
    {
      ompl_parallel_plan_.clearPlanners();
      if (ompl_simple_setup_.getPlannerAllocator())
    for (unsigned int i = 0 ; i < count ; ++i)
      ompl_parallel_plan_.addPlannerAllocator(ompl_simple_setup_.getPlannerAllocator());
      else
    for (unsigned int i = 0 ; i < count ; ++i)
      ompl_parallel_plan_.addPlanner(ompl::geometric::getDefaultPlanner(ompl_simple_setup_.getGoal()));

      ob::PlannerTerminationCondition ptc = ob::timedPlannerTerminationCondition(timeout - ompl::time::seconds(ompl::time::now() - start));
      registerTerminationCondition(ptc);
      result = ompl_parallel_plan_.solve(ptc, 1, count, true) == ompl::base::PlannerStatus::EXACT_SOLUTION;
      last_plan_time_ = ompl::time::seconds(ompl::time::now() - start);
      unregisterTerminationCondition();
    }
    else
    {
      ob::PlannerTerminationCondition ptc = ob::timedPlannerTerminationCondition(timeout - ompl::time::seconds(ompl::time::now() - start));
      registerTerminationCondition(ptc);
      int n = count / max_planning_threads_;
      result = true;
      for (int i = 0 ; i < n && ptc() == false ; ++i)
      {
    ompl_parallel_plan_.clearPlanners();
    if (ompl_simple_setup_.getPlannerAllocator())
      for (unsigned int i = 0 ; i < max_planning_threads_ ; ++i)
        ompl_parallel_plan_.addPlannerAllocator(ompl_simple_setup_.getPlannerAllocator());
    else
      for (unsigned int i = 0 ; i < max_planning_threads_ ; ++i)
        ompl_parallel_plan_.addPlanner(og::getDefaultPlanner(ompl_simple_setup_.getGoal()));
    bool r = ompl_parallel_plan_.solve(ptc, 1, max_planning_threads_, true) == ompl::base::PlannerStatus::EXACT_SOLUTION;
    result = result && r;
      }
      n = count % max_planning_threads_;
      if (n && ptc() == false)
      {
    ompl_parallel_plan_.clearPlanners();
    if (ompl_simple_setup_.getPlannerAllocator())
      for (int i = 0 ; i < n ; ++i)
        ompl_parallel_plan_.addPlannerAllocator(ompl_simple_setup_.getPlannerAllocator());
    else
      for (int i = 0 ; i < n ; ++i)
        ompl_parallel_plan_.addPlanner(og::getDefaultPlanner(ompl_simple_setup_.getGoal()));
    bool r = ompl_parallel_plan_.solve(ptc, 1, n, true) == ompl::base::PlannerStatus::EXACT_SOLUTION;
    result = result && r;
      }
      last_plan_time_ = ompl::time::seconds(ompl::time::now() - start);
      unregisterTerminationCondition();
    }
  }

  postSolve();

  return result;
}

void ompl_interface::ModelBasedPlanningContext::registerTerminationCondition(const ob::PlannerTerminationCondition &ptc)
{
  boost::mutex::scoped_lock slock(ptc_lock_);
  ptc_ = &ptc;
}

void ompl_interface::ModelBasedPlanningContext::unregisterTerminationCondition()
{
  boost::mutex::scoped_lock slock(ptc_lock_);
  ptc_ = NULL;
}

bool ompl_interface::ModelBasedPlanningContext::terminate()
{
  boost::mutex::scoped_lock slock(ptc_lock_);
  if (ptc_)
    ptc_->terminate();
  return true;
}