types_implementation.cpp

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#include <mtt/types_declaration.h>

void constant_velocity_ekfilter::SetIdentity(Matrix& M,int size,double value)
{
        for(int l=0;l<size;l++)
                for(int c=0;c<size;c++)
                        if(c==l)
                                M(l,c)=value;
                        else
                                M(l,c)=0;
}

void constant_velocity_ekfilter::SetZero(Matrix& M,int size)
{
        for(int l=0;l<size;l++)
                for(int c=0;c<size;c++)
                        M(l,c)=0;
}

void constant_velocity_ekfilter::InitFilter(Vector4d& x_init)
{
        setDim(4,0,4,2,2);
        dt=0;
        lt=Time::now();
        
        Vector x_0(4);

        x_0(0)=x_init(0);//x
        x_0(1)=x_init(1);//y
        x_0(2)=x_init(2);//vx
        x_0(3)=x_init(3);//vy
        
        Matrix P_0(4,4);
        
        SetIdentity(P_0,4,10.);

        init(x_0,P_0);
}

void constant_velocity_ekfilter::makeCommonProcess()
{
//      dt=Time::now().toSec()-lt.toSec();
//      lt=Time::now();
        dt=1./50.;              
}

void constant_velocity_ekfilter::makeBaseA()
{
        A(0,0)=1.0;
        A(0,1)=0.0;
//      A(0,2)=dt;
        A(0,3)=0.0;

        A(1,0)=0.0;
        A(1,1)=1.0;
        A(1,2)=0.0;
//      A(1,3)=dt;
        
        A(2,0)=0.0;
        A(2,1)=0.0;
        A(2,2)=1.0;
        A(2,3)=0.0;
        
        A(3,0)=0.0;
        A(3,1)=0.0;
        A(3,2)=0.0;
        A(3,3)=1.0;
}

void constant_velocity_ekfilter::makeA()
{
        A(0,2)=dt;
        A(1,3)=dt;
}

void constant_velocity_ekfilter::makeBaseH()
{
        H(0,0) = 1.0;
        H(1,1) = 1.0;
}

void constant_velocity_ekfilter::makeBaseW()
{
        SetIdentity(W,4,1.0);
}

void constant_velocity_ekfilter::makeBaseV()
{
        SetIdentity(V,2,1.0);
}

void constant_velocity_ekfilter::makeR()
{
        double dir = atan2(dz(1),dz(0));
        
        Matrix2d eigval;
        Matrix2d eigvct;
        
        double magnitude = sqrt(dz(1)*dz(1)+dz(0)*dz(0));
        
        //for a small error i want a circle, for a large one i want a ellipse
        //small error val1=val2, big error val1>val2
        
        double max_v=0.1;
        double min_v=0.005;
        
        double nv = ((min_v - max_v)/max_v)*magnitude + max_v;
        nv=nv>min_v?nv:min_v;
        
//      cout<<"Nv:"<<nv<<endl;
//      cout<<"dir:"<<dir<<endl;
        eigval << max_v, 0,
                                0,  nv;

        eigvct << 1, 0,
                                0, 1;
                                
        Matrix2d rot; 
        rot << cos(dir), sin(dir),
                        -sin(dir), cos(dir);

        eigvct= eigvct*rot;
                        
        Matrix2d cov = eigvct*eigval*eigvct.inverse();
                                        
        R(0,0) = cov(0,0);
        R(0,1) = cov(0,1);

        R(1,0) = cov(1,0);
        R(1,1) = cov(1,1);
}

void constant_velocity_ekfilter::makeQ()
{
        SetZero(Q,4);
        double sigma=10.;
        double factor=pow(sigma,2)*dt/6.;

        Q(0,0)=factor*2*pow(dt,2);//x x
        Q(1,1)=factor*2*pow(dt,2);//y y
        
        Q(0,2)=factor*3*pow(dt,1);//x vx
        Q(2,1)=factor*3*pow(dt,1);//vx v
        
        Q(1,3)=factor*3*pow(dt,1);//y vy
        Q(3,1)=factor*3*pow(dt,1);//vy y
        
        Q(2,2)=factor*6;//vx vx
        Q(3,3)=factor*6;//vy vy
}

void constant_velocity_ekfilter::makeProcess()
{
        Vector x_(x.size());
        
        x_(0) = x(0) + x(2)*dt;//X
        x_(1) = x(1) + x(3)*dt;//Y
        x_(2) = x(2);//Vx
        x_(3) = x(3);//Vy

        x.swap(x_);
}

void constant_velocity_ekfilter::makeMeasure()
{
        z(0)=x(0); //X
        z(1)=x(1); //Y
}

t_point::t_point()
{
        x=0;
        y=0;
        z=0;
        r=0;
        t=0;
        n=0;
        ni=0;
}
                
void t_point::SetZero()
{
        x=0;
        y=0;
        z=0;
        r=0;
        t=0;
        n=0;
        ni=0;
}

t_point& t_point::operator+=(const t_point &rhs)
{
        x+=rhs.x;
        y+=rhs.y;
        z+=rhs.z;
        r+=rhs.r;
        t+=rhs.t;
        
        return *this;
}
                
void t_point::Scale(double val)
{
        x*=val;
        y*=val;
        z*=val;
        r*=val;
        t*=val;
}


t_cluster::t_cluster()
{
        id=0;
        
//      points.clear();
//      associations.clear();
}

t_cluster& t_cluster::operator=(const t_cluster &rhs)
{
        id=rhs.id;
        centroid=rhs.centroid;
        
        t_pointPtr p;
        
        for(uint i=0;i<rhs.points.size();i++)
        {
                p.reset(new t_point);
                *p=*(rhs.points[i]);
                
                points.push_back(p);
        }
        
        return *this;
}
                
bool t_cluster::BreakPointDetector(t_pointPtr&pt,t_pointPtr&pt_m1)
{
        double d = sqrt( pow(pt->x-pt_m1->x,2) + pow(pt->y-pt_m1->y,2));
        
        if(d>2.0)
                return true;
        
        return false;
}

void t_cluster::CalculateCentroid(void)
{
        centroid.SetZero();
        
        for(uint i=0;i<points.size();i++)
                centroid+=*points[i];
        
        centroid.Scale(1./points.size());
}


void t_node::IncreaseAge(int increment)
{
        age+=increment;
}

void t_node::Step()
{
        Vector u(0);
        Vector x_(4);
        
        //Convert from eigen format to ekfilter
        Vector z_(2);
        z_(0)=z(0);
        z_(1)=z(1);
        
        //Makes one prediction-correction step
        estimator.step(u,z_);
        
        //Returns the corrected state (a posteriori state estimate)
        x_=estimator.getX();
        
        //Convert from ekfilter to eigen format
        x(0)=x_(0);
        x(1)=x_(1);
        x(2)=x_(2);
        x(3)=x_(3);
        
        //Returns the a posteriori error covariance estimate matrix
        Matrix P_=estimator.calculateP();
        
        //Convert from ekfilter to eigen format
        P(0,0)=P_(0,0);
        P(0,1)=P_(0,1);
        P(0,2)=P_(0,2);
        P(0,3)=P_(0,3);
        
        P(1,0)=P_(1,0);
        P(1,1)=P_(1,1);
        P(1,2)=P_(1,2);
        P(1,3)=P_(1,3);
        
        P(2,0)=P_(2,0);
        P(2,1)=P_(2,1);
        P(2,2)=P_(2,2);
        P(2,3)=P_(2,3);
        
        P(3,0)=P_(3,0);
        P(3,1)=P_(3,1);
        P(3,2)=P_(3,2);
        P(3,3)=P_(3,3);

        //Returns the predicted state vector (a priori state estimate)
        Vector x_p_=estimator.predict(u);
        
        //Convert from ekfilter to eigen format
        x_p(0)=x_p_(0);
        x_p(1)=x_p_(1);
        x_p(2)=x_p_(2);
        x_p(3)=x_p_(3);
}

void t_node::CommonConstructor()
{
        //Step on the new measurements
        Step();
}
                
t_node::t_node(t_cluster&cluster,long iteration)
{
        mode=NEW;
        
        failed_associations_counter=0;
        successful_association_counter=1;
        age=0;
        
        id=cluster.id;
        data_iteration=iteration;
        
        local_cluster=cluster;
        
        cluster.associations.push_back(id);     
        
        z(0)=local_cluster.centroid.x;//x position measurement
        z(1)=local_cluster.centroid.y;//y position measurement
        
        Vector4d x_init;
        
        x_init(0)=z(0);
        x_init(1)=z(1);
        x_init(2)=0;
        x_init(3)=0;
        
        estimator.InitFilter(x_init);
        
        CommonConstructor();
}
                        
t_node::t_node(t_node&node,t_cluster&cluster,long iteration)
{
        mode=MAIN;
        
        failed_associations_counter=node.failed_associations_counter;
        successful_association_counter=node.successful_association_counter+1;
        age=0;
        
        id=node.id;
        data_iteration=iteration;
        
        cluster.associations.push_back(id);
        local_cluster=cluster;
        
        estimator=node.estimator;//i don't know if this works
        
        z(0)=local_cluster.centroid.x;
        z(1)=local_cluster.centroid.y;
        
        CommonConstructor();
}

t_node::t_node(t_node&node,long iteration)
{       
        mode=FAILED;
        
        failed_associations_counter=node.failed_associations_counter;
        failed_associations_counter++;
        age=0;
        
        successful_association_counter=node.successful_association_counter;
        
        id=node.id;
        data_iteration=iteration;
        
        local_cluster=node.local_cluster;
        
        estimator=node.estimator;
        
        //Use the previous node predicted position as measurement
        z(0)=node.x_p(0);
        z(1)=node.x_p(1);
        
        CommonConstructor();
}

t_node::~t_node(void)
{
//      cout<<"Erase this shit:"<<GetName()<<endl;
}

string t_node::GetName()
{
        return "N"+ boost::lexical_cast<string>(id) + ".(" + boost::lexical_cast<string>(data_iteration) + ")";
//      return "N"+ boost::lexical_cast<string>(id) + "." + boost::lexical_cast<string>(age) + ".(" + boost::lexical_cast<string>(data_iteration) + ")";
}

ostream& operator<< (ostream &o, const t_nodePtr &i)
{
        return o << i->GetName();

}