motionmodel.cpp

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#include "gmapping/gridfastslam/motionmodel.h"
#include <gmapping/utils/stat.h>
#include <iostream>
 
#define MotionModelConditioningLinearCovariance 0.01
#define MotionModelConditioningAngularCovariance 0.001
 
namespace GMapping {
 
 
 
OrientedPoint 
MotionModel::drawFromMotion (const OrientedPoint& p, double linearMove, double angularMove) const{
        OrientedPoint n(p);
        double lm=linearMove  + fabs( linearMove ) * sampleGaussian( srr ) + fabs( angularMove ) * sampleGaussian( str );
        double am=angularMove + fabs( linearMove ) * sampleGaussian( srt ) + fabs( angularMove ) * sampleGaussian( stt );
        n.x+=lm*cos(n.theta+.5*am);
        n.y+=lm*sin(n.theta+.5*am);
        n.theta+=am;
        n.theta=atan2(sin(n.theta), cos(n.theta));
        return n;
}
 
OrientedPoint 
MotionModel::drawFromMotion(const OrientedPoint& p, const OrientedPoint& pnew, const OrientedPoint& pold) const{
        double sxy=0.3*srr;
        OrientedPoint delta=absoluteDifference(pnew, pold);
        OrientedPoint noisypoint(delta);
        noisypoint.x+=sampleGaussian(srr*fabs(delta.x)+str*fabs(delta.theta)+sxy*fabs(delta.y));
        noisypoint.y+=sampleGaussian(srr*fabs(delta.y)+str*fabs(delta.theta)+sxy*fabs(delta.x));
        noisypoint.theta+=sampleGaussian(stt*fabs(delta.theta)+srt*sqrt(delta.x*delta.x+delta.y*delta.y));
        noisypoint.theta=fmod(noisypoint.theta, 2*M_PI);
        if (noisypoint.theta>M_PI)
                noisypoint.theta-=2*M_PI;
        return absoluteSum(p,noisypoint);
}
 
 
/*
OrientedPoint 
MotionModel::drawFromMotion(const OrientedPoint& p, const OrientedPoint& pnew, const OrientedPoint& pold) const{
        
        //compute the three stps needed for perfectly matching the two poses if the noise is absent
        
        OrientedPoint delta=pnew-pold;
        double aoffset=atan2(delta.y, delta.x);
        double alpha1=aoffset-pold.theta;
        alpha1=atan2(sin(alpha1), cos(alpha1));
        double rho=sqrt(delta*delta);
        double alpha2=pnew.theta-aoffset;
        alpha2=atan2(sin(alpha2), cos(alpha2));
        
        OrientedPoint pret=drawFromMotion(p, 0, alpha1);
        pret=drawFromMotion(pret, rho, 0);
        pret=drawFromMotion(pret, 0, alpha2);
        return pret;
}
*/
 
 
Covariance3 MotionModel::gaussianApproximation(const OrientedPoint& pnew, const OrientedPoint& pold) const{
        OrientedPoint delta=absoluteDifference(pnew,pold);
        double linearMove=sqrt(delta.x*delta.x+delta.y*delta.y);
        double angularMove=fabs(delta.x);
        double s11=srr*srr*linearMove*linearMove;
        double s22=stt*stt*angularMove*angularMove;
        double s12=str*angularMove*srt*linearMove;
        Covariance3 cov;
        double s=sin(pold.theta),c=cos(pold.theta);
        cov.xx=c*c*s11+MotionModelConditioningLinearCovariance;
        cov.yy=s*s*s11+MotionModelConditioningLinearCovariance;
        cov.tt=s22+MotionModelConditioningAngularCovariance;
        cov.xy=s*c*s11;
        cov.xt=c*s12;
        cov.yt=s*s12;
        return cov;
}
 
};