CActionRobotMovement3D.cpp

Go to the documentation of this file.

/* +---------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)               |
   |                          http://www.mrpt.org/                             |
   |                                                                           |
   | Copyright (c) 2005-2017, Individual contributors, see AUTHORS file        |
   | See: http://www.mrpt.org/Authors - All rights reserved.                   |
   | Released under BSD License. See details in http://www.mrpt.org/License    |
   +---------------------------------------------------------------------------+ */
 
#include "obs-precomp.h"   // Precompiled headers
 
#include <mrpt/random.h>
#include <mrpt/utils/CStream.h>
#include <mrpt/obs/CActionRobotMovement3D.h>
#include <mrpt/poses/CPose3DPDFParticles.h>
 
using namespace mrpt;
using namespace mrpt::obs;
using namespace mrpt::utils;
using namespace mrpt::poses;
using namespace mrpt::random;
using namespace mrpt::utils;
 
IMPLEMENTS_SERIALIZABLE(CActionRobotMovement3D, CAction, mrpt::obs)
 
/*---------------------------------------------------------------
                                                Constructor
  ---------------------------------------------------------------*/
CActionRobotMovement3D::CActionRobotMovement3D() :
        poseChange(),
        rawOdometryIncrementReading(),
        estimationMethod( emOdometry ),
        motionModelConfiguration(),
        hasVelocities(6,false),
        velocities(6)
{
        velocities.assign(.0);
}
 
 
/*---------------------------------------------------------------
  Implements the writing to a CStream capability of CSerializable objects
 ---------------------------------------------------------------*/
void  CActionRobotMovement3D::writeToStream(mrpt::utils::CStream &out, int *version) const
{
        if (version)
                *version = 1;
        else
        {
                uint32_t                i  = static_cast<uint32_t>( estimationMethod );
 
                out << i;
 
                // The PDF:
                out << poseChange;
 
                out << hasVelocities << velocities;
 
                out << timestamp;
        }
}
 
/*---------------------------------------------------------------
  Implements the reading from a CStream capability of CSerializable objects
 ---------------------------------------------------------------*/
void  CActionRobotMovement3D::readFromStream(mrpt::utils::CStream &in, int version)
{
        switch(version)
        {
        case 0:
        case 1:
                {
                        uint32_t        i;
 
                        // Read the estimation method first:
                        in >> i;
                        estimationMethod = static_cast<TEstimationMethod>(i);
 
                        in >> poseChange;
                        in >> hasVelocities >> velocities;
 
                        if (version>=1)
                                        in >> timestamp;
                        else    timestamp = INVALID_TIMESTAMP;
                } break;
        default:
                MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(version)
 
        };
 
}
 
 
void  CActionRobotMovement3D::computeFromOdometry(
        const CPose3D                           &odometryIncrement,
        const TMotionModelOptions       &options)
{
        // Set the members data:
        estimationMethod                        = emOdometry;
        rawOdometryIncrementReading     = odometryIncrement;
        motionModelConfiguration        = options;
 
        if ( options.modelSelection == mm6DOF )
                                computeFromOdometry_model6DOF( odometryIncrement, options );
}
 
 
/*---------------------------------------------------------------
                                                TMotionModelOptions
 ---------------------------------------------------------------*/
CActionRobotMovement3D::TMotionModelOptions::TMotionModelOptions() :
modelSelection(mm6DOF),
        mm6DOFModel()
{
 
        mm6DOFModel.nParticlesCount             = 300;
        mm6DOFModel.a1          = 0.05f;
        mm6DOFModel.a2          = 0.05f;
        mm6DOFModel.a3          = 0.05f;
        mm6DOFModel.a4          = 0.05f;
        mm6DOFModel.a5          = 0.05f;
        mm6DOFModel.a6          = 0.05f;
        mm6DOFModel.a7          = 0.05f;
        mm6DOFModel.a8          = 0.05f;
        mm6DOFModel.a9          = 0.05f;
        mm6DOFModel.a10         = 0.05f;
        mm6DOFModel.additional_std_XYZ  = 0.001f;
        mm6DOFModel.additional_std_angle        = DEG2RAD(0.05f);
 
}
 
/*---------------------------------------------------------------
                                computeFromOdometry_model6DOF
        ---------------------------------------------------------------*/
void  CActionRobotMovement3D::computeFromOdometry_model6DOF(
        const CPose3D                           &odometryIncrement,
        const TMotionModelOptions       &o
        )
{
        // The Gaussian PDF:
        // ---------------------------
        CPose3DPDFParticles             *aux;
        static CPose3D                  nullPose(0,0,0,0,0,0);
 
        mrpt::poses::CPose3DPDFPtr poseChangeTemp = CPose3DPDFParticles::Create();
        aux = static_cast<CPose3DPDFParticles*>( poseChangeTemp.pointer() );
 
        // Set the number of particles:
        aux->resetDeterministic(nullPose, o.mm6DOFModel.nParticlesCount );
 
        //The motion model: A. L. Ballardini, A. Furlan, A. Galbiati, M. Matteucci, F. Sacchi, D. G. Sorrenti An effective 6DoF motion model for 3D-6DoF Monte Carlo Localization 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles, IROS, 2012
 
        /*
                The brief description:
                Find XYZ deltas: dX=x(t)-x(t-1); dY=y(t)-y(t-1); dZ=z(t)-z(t-1)
                Find angular deltas (normalised): dRoll=roll(t)-roll(t-1); dPitch=pitch(t)-pitch(t-1); dYaw=yaw(t)-yaw(t-1)
 
                Here t - is time step
 
                 Calculate the odometry for 6DOF:
 
 
                                yaw1 = atan2 (dY,dX)
                                pitch1 = atan2 (dZ , sqrt(dX^2 + dY^2 + dZ^2) )
                                trans = sqrt(dX^2 + dY^2 + dZ^2)
                                roll = dRoll
                                yaw2= dYaw
                                pitch2= dPitch
 
 
                Model the error:
 
 
                                yaw1_draw = yaw1 + sample(a1 * yaw1 + a2 * trans )
                                pitch1_draw = pitch1 + sample(a3 * dZ )
                                trans_draw = trans + sample( a4 * trans + a5 * yaw2 + a6 * (roll + pitch2 ) )
                                roll_draw = roll + sample(a7 * roll)
                                pitch2_draw = pitch2 + sample(a8 * pitch2 )
                                yaw2_draw = yaw2 + sample(a9 * yaw2 + a10 * trans )
 
                 Here sample() - sampling from zero mean Gaussian distribution
 
                Calculate the spherical coordinates:
                                x = trans_draw * sin( pitch1_draw ) * cos ( yaw1_draw )
                                y = trans_draw * sin( pitch1_draw ) * sin ( yaw1_draw )
                                z = trans_draw * cos( pitch1_draw )
                 roll = roll_draw
                pitch = pitch1_draw + pitch2_draw
                        yaw = yaw1_draw + yaw2_draw
 
                normalize_angle(roll, pitch, yaw )
        */
 
 
        // The increments in odometry:
        float   Ayaw1   = ( odometryIncrement.y()!=0 || odometryIncrement.x()!=0) ?
                                                atan2( odometryIncrement.y(), odometryIncrement.x() ) : 0;
 
        float    Atrans = odometryIncrement.norm();
 
        float   Apitch1 = ( odometryIncrement.y()!=0 || odometryIncrement.x()!=0 || odometryIncrement.z()!=0) ?
                                                atan2( odometryIncrement.z(),   odometryIncrement.norm()) : 0;
 
        float Aroll =   odometryIncrement.roll();
        float Apitch2 = odometryIncrement.pitch();
        float Ayaw2 = odometryIncrement.yaw();
 
 
 
        // Draw samples:
        for (size_t i=0;i<o.mm6DOFModel.nParticlesCount;i++)
        {
                float   Ayaw1_draw      = Ayaw1 + (o.mm6DOFModel.a1*Ayaw1 +o.mm6DOFModel.a2*Atrans ) * randomGenerator.drawGaussian1D_normalized();
                float   Apitch1_draw= Apitch1 + (o.mm6DOFModel.a3*odometryIncrement.z())* randomGenerator.drawGaussian1D_normalized();
                float   Atrans_draw = Atrans + (o.mm6DOFModel.a4*Atrans+ o.mm6DOFModel.a5*Ayaw2+ o.mm6DOFModel.a6*(Aroll+Apitch2)) * randomGenerator.drawGaussian1D_normalized();
 
                float Aroll_draw=Aroll+(o.mm6DOFModel.a7*Aroll) * randomGenerator.drawGaussian1D_normalized();
                float Apitch2_draw=Apitch2+(o.mm6DOFModel.a8*Apitch2)* randomGenerator.drawGaussian1D_normalized();
                float Ayaw2_draw=Ayaw2 +(o.mm6DOFModel.a9*Ayaw2+o.mm6DOFModel.a10*Atrans)* randomGenerator.drawGaussian1D_normalized();
 
                // Output:
                aux->m_particles[i].d->x( Atrans_draw * sin( Apitch1_draw )*cos(Ayaw1_draw) + motionModelConfiguration.mm6DOFModel.additional_std_XYZ * randomGenerator.drawGaussian1D_normalized() );
                aux->m_particles[i].d->y( Atrans_draw * sin( Apitch1_draw )*sin(Ayaw1_draw) + motionModelConfiguration.mm6DOFModel.additional_std_XYZ * randomGenerator.drawGaussian1D_normalized() );
                aux->m_particles[i].d->z( Atrans_draw * cos( Apitch1_draw ) + motionModelConfiguration.mm6DOFModel.additional_std_XYZ * randomGenerator.drawGaussian1D_normalized() );
 
 
                double new_yaw= Ayaw1_draw + Ayaw2_draw + motionModelConfiguration.mm6DOFModel.additional_std_angle * randomGenerator.drawGaussian1D_normalized();
                double new_pitch=       Apitch1_draw + Apitch2_draw + motionModelConfiguration.mm6DOFModel.additional_std_angle * randomGenerator.drawGaussian1D_normalized() ;
                double new_roll = Aroll_draw + motionModelConfiguration.mm6DOFModel.additional_std_angle * randomGenerator.drawGaussian1D_normalized() ;
 
                aux->m_particles[i].d->setYawPitchRoll(new_yaw,new_pitch,new_roll);
                aux->m_particles[i].d->normalizeAngles();
 
        }
 
                poseChange.copyFrom(*poseChangeTemp);
}