C++ OMPL_INFORM函数代码示例

void ompl::geometric::RRTstar::setup()
{
    Planner::setup();
    tools::SelfConfig sc(si_, getName());
    sc.configurePlannerRange(maxDistance_);
    if (!si_->getStateSpace()->hasSymmetricDistance() || !si_->getStateSpace()->hasSymmetricInterpolate())
    {
        OMPL_WARN("%s requires a state space with symmetric distance and symmetric interpolation.", getName().c_str());
    }

    if (!nn_)
        nn_.reset(tools::SelfConfig::getDefaultNearestNeighbors<Motion*>(si_->getStateSpace()));
    nn_->setDistanceFunction(boost::bind(&RRTstar::distanceFunction, this, _1, _2));

    // Setup optimization objective
    //
    // If no optimization objective was specified, then default to
    // optimizing path length as computed by the distance() function
    // in the state space.
    if (pdef_)
    {
        if (pdef_->hasOptimizationObjective())
            opt_ = pdef_->getOptimizationObjective();
        else
        {
            OMPL_INFORM("%s: No optimization objective specified. Defaulting to optimizing path length for the allowed planning time.", getName().c_str());
            opt_.reset(new base::PathLengthOptimizationObjective(si_));
        }
    }
    else
    {
        OMPL_INFORM("%s: problem definition is not set, deferring setup completion...", getName().c_str());
        setup_ = false;
    }
}

void ompl::geometric::CForest::setup()
{
    Planner::setup();
    if (pdef_->hasOptimizationObjective())
        opt_ = pdef_->getOptimizationObjective();
    else
    {
        OMPL_INFORM("%s: No optimization objective specified. Defaulting to optimizing path length for the allowed "
                    "planning time.",
                    getName().c_str());
        opt_ = std::make_shared<base::PathLengthOptimizationObjective>(si_);
    }

    bestCost_ = opt_->infiniteCost();

    if (planners_.empty())
    {
        OMPL_INFORM("%s: Number and type of instances not specified. Defaulting to %d instances of RRTstar.",
                    getName().c_str(), numThreads_);
        addPlannerInstances<RRTstar>(numThreads_);
    }

    for (auto &planner : planners_)
        if (!planner->isSetup())
            planner->setup();

    // This call is needed to make sure the ParamSet is up to date after changes induced by the planner setup calls
    // above, via the state space wrappers for CForest.
    si_->setup();
}

bool ompl::tools::LightningDB::load(const std::string &fileName)
{
    // Error checking
    if (fileName.empty())
    {
        OMPL_ERROR("Empty filename passed to save function");
        return false;
    }
    if ( !boost::filesystem::exists( fileName ) )
    {
        OMPL_WARN("Database file does not exist: %s", fileName.c_str());
        return false;
    }

    // Load database from file, track loading time
    time::point start = time::now();

    OMPL_INFORM("Loading database from file: %s", fileName.c_str());

    // Open a binary input stream
    std::ifstream iStream(fileName.c_str(), std::ios::binary);

    // Get the total number of paths saved
    double numPaths = 0;
    iStream >> numPaths;

    // Check that the number of paths makes sense
    if (numPaths < 0 || numPaths > std::numeric_limits<double>::max())
    {
        OMPL_WARN("Number of paths to load %d is a bad value", numPaths);
        return false;
    }

    // Start loading all the PlannerDatas
    for (std::size_t i = 0; i < numPaths; ++i)
    {
        // Create a new planner data instance
        ompl::base::PlannerDataPtr plannerData(new ompl::base::PlannerData(si_));

        // Note: the StateStorage class checks if the states match for us
        plannerDataStorage_.load(iStream, *plannerData.get());

        // Add to nearest neighbor tree
        nn_->add(plannerData);
    }

    // Close file
    iStream.close();

    double loadTime = time::seconds(time::now() - start);
    OMPL_INFORM("Loaded database from file in %f sec with %d paths", loadTime, nn_->size());
    return true;
}

// we provide a duplicate implementation here to allow the planner to choose how the time is turned into a planner termination condition
ompl::base::PlannerStatus ompl::control::SimpleSetup::solve(double time)
{
    setup();
    last_status_ = base::PlannerStatus::UNKNOWN;
    time::point start = time::now();
    last_status_ = planner_->solve(time);
    planTime_ = time::seconds(time::now() - start);
    if (last_status_)
        OMPL_INFORM("Solution found in %f seconds", planTime_);
    else
        OMPL_INFORM("No solution found after %f seconds", planTime_);
    return last_status_;
}

ompl::base::PlannerStatus ompl::geometric::SimpleSetup::solve(const base::PlannerTerminationCondition &ptc)
{
    setup();
    lastStatus_ = base::PlannerStatus::UNKNOWN;
    time::point start = time::now();
    lastStatus_ = planner_->solve(ptc);
    planTime_ = time::seconds(time::now() - start);
    if (lastStatus_)
        OMPL_INFORM("Solution found in %f seconds", planTime_);
    else
        OMPL_INFORM("No solution found after %f seconds", planTime_);
    return lastStatus_;
}

void ompl::geometric::RRTXstatic::setup()
{
    Planner::setup();
    tools::SelfConfig sc(si_, getName());
    sc.configurePlannerRange(maxDistance_);
    if (!si_->getStateSpace()->hasSymmetricDistance() || !si_->getStateSpace()->hasSymmetricInterpolate())
    {
        OMPL_WARN("%s requires a state space with symmetric distance and symmetric interpolation.", getName().c_str());
    }

    if (!nn_)
        nn_.reset(tools::SelfConfig::getDefaultNearestNeighbors<Motion *>(this));
    nn_->setDistanceFunction([this](const Motion *a, const Motion *b) { return distanceFunction(a, b); });

    // Setup optimization objective
    //
    // If no optimization objective was specified, then default to
    // optimizing path length as computed by the distance() function
    // in the state space.
    if (pdef_)
    {
        if (pdef_->hasOptimizationObjective())
            opt_ = pdef_->getOptimizationObjective();
        else
        {
            OMPL_INFORM("%s: No optimization objective specified. Defaulting to optimizing path length for the allowed "
                        "planning time.",
                        getName().c_str());
            opt_ = std::make_shared<base::PathLengthOptimizationObjective>(si_);

            // Store the new objective in the problem def'n
            pdef_->setOptimizationObjective(opt_);
        }
        mc_ = MotionCompare(opt_, pdef_);
        q_ = BinaryHeap<Motion *, MotionCompare>(mc_);
    }
    else
    {
        OMPL_INFORM("%s: problem definition is not set, deferring setup completion...", getName().c_str());
        setup_ = false;
    }

    // Calculate some constants:
    calculateRewiringLowerBounds();

    // Set the bestCost_ and prunedCost_ as infinite
    bestCost_ = opt_->infiniteCost();
}

void ompl::geometric::RRTstar::setup()
{
    Planner::setup();
    tools::SelfConfig sc(si_, getName());
    sc.configurePlannerRange(maxDistance_);
    if (!si_->getStateSpace()->hasSymmetricDistance() || !si_->getStateSpace()->hasSymmetricInterpolate())
    {
        OMPL_WARN("%s requires a state space with symmetric distance and symmetric interpolation.", getName().c_str());
    }

    if (!nn_)
        nn_.reset(tools::SelfConfig::getDefaultNearestNeighbors<Motion*>(this));
    nn_->setDistanceFunction(std::bind(&RRTstar::distanceFunction, this, std::placeholders::_1, std::placeholders::_2));

    // Setup optimization objective
    //
    // If no optimization objective was specified, then default to
    // optimizing path length as computed by the distance() function
    // in the state space.
    if (pdef_)
    {
        if (pdef_->hasOptimizationObjective())
            opt_ = pdef_->getOptimizationObjective();
        else
        {
            OMPL_INFORM("%s: No optimization objective specified. Defaulting to optimizing path length for the allowed planning time.", getName().c_str());
            opt_.reset(new base::PathLengthOptimizationObjective(si_));

            // Store the new objective in the problem def'n
            pdef_->setOptimizationObjective(opt_);
        }
    }
    else
    {
        OMPL_INFORM("%s: problem definition is not set, deferring setup completion...", getName().c_str());
        setup_ = false;
    }

    // Get the measure of the entire space:
    prunedMeasure_ = si_->getSpaceMeasure();

    // Calculate some constants:
    calculateRewiringLowerBounds();

    // Set the bestCost_ and prunedCost_ as infinite
    bestCost_ = opt_->infiniteCost();
    prunedCost_ = opt_->infiniteCost();
}

bool ompl::tools::ThunderDB::addPath(ompl::geometric::PathGeometric &solutionPath, double &insertionTime)
{
    // Error check
    if (!spars_)
    {
        OMPL_ERROR("SPARSdb planner has not been passed into the ThunderDB yet");
        insertionTime = 0;
        return false;
    }

    // Prevent inserting into database
    if (!saving_enabled_)
    {
        OMPL_WARN("ThunderDB: Saving is disabled so not adding path");
        return false;
    }

    bool result;
    double seconds = 120;  // 10; // a large number, should never need to use this
    ompl::base::PlannerTerminationCondition ptc = ompl::base::timedPlannerTerminationCondition(seconds, 0.1);

    // Benchmark runtime
    time::point startTime = time::now();
    {
        result = spars_->addPathToRoadmap(ptc, solutionPath);
    }
    insertionTime = time::seconds(time::now() - startTime);

    OMPL_INFORM("SPARSdb now has %d states", spars_->getNumVertices());

    // Record this new addition
    numPathsInserted_++;

    return result;
}

void ompl::geometric::SPARStwo::setup()
{
    Planner::setup();
    if (!nn_)
        nn_.reset(tools::SelfConfig::getDefaultNearestNeighbors<Vertex>(si_->getStateSpace()));
    nn_->setDistanceFunction(boost::bind(&SPARStwo::distanceFunction, this, _1, _2));
    double maxExt = si_->getMaximumExtent();
    sparseDelta_ = sparseDeltaFraction_ * maxExt;
    denseDelta_ = denseDeltaFraction_ * maxExt;

    // Setup optimization objective
    //
    // If no optimization objective was specified, then default to
    // optimizing path length as computed by the distance() function
    // in the state space.
    if (pdef_)
    {
        if (pdef_->hasOptimizationObjective())
        {
            opt_ = pdef_->getOptimizationObjective();
            if (!dynamic_cast<base::PathLengthOptimizationObjective*>(opt_.get()))
                OMPL_WARN("%s: Asymptotic optimality has only been proven with path length optimizaton; convergence for other optimizaton objectives is not guaranteed.", getName().c_str());
        }
        else
            opt_.reset(new base::PathLengthOptimizationObjective(si_));
    }
    else
    {
        OMPL_INFORM("%s: problem definition is not set, deferring setup completion...", getName().c_str());
        setup_ = false;
    }
}

ompl::base::PlannerStatus ompl::geometric::CForest::solve(const base::PlannerTerminationCondition &ptc)
{
    using solveFunctionType = void (ompl::geometric::CForest::*)(base::Planner *, const base::PlannerTerminationCondition &);

    checkValidity();

    time::point start = time::now();
    std::vector<std::thread*> threads(planners_.size());
    const base::ReportIntermediateSolutionFn prevSolutionCallback = getProblemDefinition()->getIntermediateSolutionCallback();

    if (prevSolutionCallback)
        OMPL_WARN("Cannot use previously set intermediate solution callback with %s", getName().c_str());

    pdef_->setIntermediateSolutionCallback(std::bind(&CForest::newSolutionFound, this,
        std::placeholders::_1, std::placeholders::_2, std::placeholders::_3));
    bestCost_ = opt_->infiniteCost();

    // run each planner in its own thread, with the same ptc.
    for (std::size_t i = 0 ; i < threads.size() ; ++i)
        threads[i] = new std::thread(std::bind((solveFunctionType)&CForest::solve, this, planners_[i].get(), ptc));

    for (auto & thread : threads)
    {
        thread->join();
        delete thread;
    }

    // restore callback
    getProblemDefinition()->setIntermediateSolutionCallback(prevSolutionCallback);
    OMPL_INFORM("Solution found in %f seconds", time::seconds(time::now() - start));
    return base::PlannerStatus(pdef_->hasSolution(), pdef_->hasApproximateSolution());
}

void ompl::control::SimpleSetup::setup()
{
    if (!configured_ || !si_->isSetup() || !planner_->isSetup())
    {
        if (!si_->isSetup())
            si_->setup();
        if (!planner_)
        {
            if (pa_)
                planner_ = pa_(si_);
            if (!planner_)
            {
                OMPL_INFORM("No planner specified. Using default.");
                planner_ = getDefaultPlanner(getGoal());
            }
        }
        planner_->setProblemDefinition(pdef_);
        if (!planner_->isSetup())
            planner_->setup();

        params_.clear();
        params_.include(si_->params());
        params_.include(planner_->params());
        configured_ = true;
    }
}

void ompl::geometric::RRTstar::setSampleRejection(const bool reject)
{
    if (static_cast<bool>(opt_) == true)
    {
        if (opt_->hasCostToGoHeuristic() == false)
        {
            OMPL_INFORM("%s: No cost-to-go heuristic set. Informed techniques will not work well.", getName().c_str());
        }
    }

    // This option is mutually exclusive with setSampleRejection, assert that:
    if (reject == true && useInformedSampling_ == true)
    {
        OMPL_ERROR("%s: InformedSampling and SampleRejection are mutually exclusive options.", getName().c_str());
    }

    // Check if we're changing the setting of rejection sampling. If we are, we will need to create a new sampler, which we only want to do if one is already allocated.
    if (reject != useRejectionSampling_)
    {
        // Store the setting
        useRejectionSampling_ = reject;

        // If we currently have a sampler, we need to make a new one
        if (sampler_ || infSampler_)
        {
            // Reset the samplers
            sampler_.reset();
            infSampler_.reset();

            // Create the sampler
            allocSampler();
        }
    }
}

    bool plan(unsigned int start_row, unsigned int start_col, unsigned int goal_row, unsigned int goal_col)
    {
        if (!ss_)
            return false;
        ob::ScopedState<> start(ss_->getStateSpace());
        start[0] = start_row;
        start[1] = start_col;
        ob::ScopedState<> goal(ss_->getStateSpace());
        goal[0] = goal_row;
        goal[1] = goal_col;
        ss_->setStartAndGoalStates(start, goal);
        // generate a few solutions; all will be added to the goal;
        for (int i = 0 ; i < 10 ; ++i)
        {
            if (ss_->getPlanner())
                ss_->getPlanner()->clear();
            ss_->solve();
        }
        const std::size_t ns = ss_->getProblemDefinition()->getSolutionCount();
        OMPL_INFORM("Found %d solutions", (int)ns);
        if (ss_->haveSolutionPath())
        {
            ss_->simplifySolution();
            og::PathGeometric &p = ss_->getSolutionPath();
            ss_->getPathSimplifier()->simplifyMax(p);
            ss_->getPathSimplifier()->smoothBSpline(p);
            return true;
        }

            return false;
    }

bool ompl::tools::ThunderDB::saveIfChanged(const std::string &fileName)
{
    if (numPathsInserted_)
        return save(fileName);
    else
        OMPL_INFORM("Not saving because database has not changed");
    return true;
}

bool ompl::tools::ThunderDB::findNearestStartGoal(int nearestK, const base::State *start, const base::State *goal,
                                                  ompl::geometric::SPARSdb::CandidateSolution &candidateSolution,
                                                  const base::PlannerTerminationCondition &ptc)
{
    bool result = spars_->getSimilarPaths(nearestK, start, goal, candidateSolution, ptc);

    if (!result)
    {
        OMPL_INFORM("RETRIEVE COULD NOT FIND SOLUTION ");
        OMPL_INFORM("spars::getSimilarPaths() returned false - retrieve could not find solution");
        return false;
    }

    OMPL_INFORM("spars::getSimilarPaths() returned true - found a solution of size %d",
                candidateSolution.getStateCount());
    return true;
}