ompl-demos 1.0.0+ds2-1build1 / usr / share / ompl / demos / RigidBodyPlanningWithIK.cpp

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/* Author: Ioan Sucan */

#include <ompl/base/spaces/SE3StateSpace.h>
#include <ompl/geometric/SimpleSetup.h>
#include <ompl/base/goals/GoalLazySamples.h>
#include <ompl/geometric/GeneticSearch.h>

#include <ompl/config.h>
#include <iostream>

namespace ob = ompl::base;
namespace og = ompl::geometric;

/// @cond IGNORE
// describe an arbitrary representation of a goal region in SE(3)
class MyGoalRegion : public ob::GoalRegion
{
public:

    MyGoalRegion(const ob::SpaceInformationPtr &si) : ob::GoalRegion(si)
    {
        setThreshold(1e-2);
    }

    virtual double distanceGoal(const ob::State *state) const
    {
        // goal region is given by states where x + y = z and orientation is close to identity
        double d = fabs(state->as<ob::SE3StateSpace::StateType>()->getX()
                        + state->as<ob::SE3StateSpace::StateType>()->getY()
                        - state->as<ob::SE3StateSpace::StateType>()->getZ())
            + fabs(state->as<ob::SE3StateSpace::StateType>()->rotation().w - 1.0);
        return d;
    }

};

// Goal regions such as the one above cannot be sampled, so
// bi-directional trees cannot be used for solving. However, we can
// transform such goal regions into ones that can be sampled. The
// caveat is that it should be possible to find states in this region
// with some other algorithm. Genetic algorithms that essentially
// perform inverse kinematics in the general sense can be used:

bool regionSamplingWithGS(const ob::SpaceInformationPtr &si, const ob::ProblemDefinitionPtr &pd, const ob::GoalRegion *region, const ob::GoalLazySamples *gls, ob::State *result)
{
    og::GeneticSearch g(si);

    // we can use a larger time duration for solve(), but we want to demo the ability
    // of GeneticSearch to continue from where it left off
    bool cont = false;
    for (int i = 0 ; i < 100 ; ++i)
        if (g.solve(0.05, *region, result))
        {
            cont = true;
            break;
        }

    if (cont)
    {
        std::cout << "Found goal state: " << std::endl;
        si->printState(result);
    }

    // we continue sampling while we are able to find solutions, we have found not more than 2 previous solutions and we have not yet solved the problem
    return cont && gls->maxSampleCount() < 3 && !pd->hasSolution();
}

void planWithIK(void)
{
    // construct the state space we are planning in
    ob::StateSpacePtr space(new ob::SE3StateSpace());

    // set the bounds for the R^3 part of SE(3)
    ob::RealVectorBounds bounds(3);
    bounds.setLow(-1);
    bounds.setHigh(1);

    space->as<ob::SE3StateSpace>()->setBounds(bounds);

    // define a simple setup class
    og::SimpleSetup ss(space);

    // create a random start state
    ob::ScopedState<ob::SE3StateSpace> start(space);
    start->setXYZ(0, 0, 0);
    start->rotation().setIdentity();
    ss.addStartState(start);

    // define our goal region
    MyGoalRegion region(ss.getSpaceInformation());

    // bind a sampling function that fills its argument with a sampled state and returns true while it can produce new samples
    // we don't need to check if new samples are different from ones previously computed as this is pefromed automatically by GoalLazySamples
    ob::GoalSamplingFn samplingFunction = boost::bind(&regionSamplingWithGS, ss.getSpaceInformation(), ss.getProblemDefinition(), &region, _1, _2);

    // create an instance of GoalLazySamples:
    ob::GoalPtr goal(new ob::GoalLazySamples(ss.getSpaceInformation(), samplingFunction));

    // we set a goal that is sampleable, but it in fact corresponds to a region that is not sampleable by default
    ss.setGoal(goal);

    // attempt to solve the problem
    ob::PlannerStatus solved = ss.solve(3.0);

    if (solved)
    {
        std::cout << "Found solution:" << std::endl;
        // print the path to screen
        ss.simplifySolution();
        ss.getSolutionPath().print(std::cout);
    }
    else
        std::cout << "No solution found" << std::endl;

    // the region variable will now go out of scope. To make sure it is not used in the sampling function any more
    // (i.e., the sampling thread was able to terminate), we make sure sampling has terminated
    goal->as<ob::GoalLazySamples>()->stopSampling();
}
/// @endcond

int main(int, char **)
{
    std::cout << "OMPL version: " << OMPL_VERSION << std::endl;

    planWithIK();

    return 0;
}