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InformationGainPURPOSE
Information gain by closing a loop with a previous pose.
SYNOPSIS
function ig=InformationGain(F,R,step)
DESCRIPTION
Information gain by closing a loop with a previous pose. Computes the information gain of stablishing a link between the current robot's and that at time 'step' with a sensor with noise R. We take the natural logarithm and, thus, the output is given in nats. Just use log2 to the it in bits. If you do so you will need to adjust the information gain parameters accordingly. CROSS-REFERENCE INFORMATION
This function calls:
SOURCE CODE
0001 function ig=InformationGain(F,R,step) 0002 % Information gain by closing a loop with a previous pose. 0003 % 0004 % Computes the information gain of stablishing a link between the current 0005 % robot's and that at time 'step' with a sensor with noise R. 0006 % 0007 % We take the natural logarithm and, thus, the output is given in nats. 0008 % Just use log2 to the it in bits. If you do so you will need to 0009 % adjust the information gain parameters accordingly. 0010 0011 MarginalSigma=GetMarginalCovariance(F,step); 0012 0013 PoseN=Pose(GetPoseMean(F,F.nSteps)); 0014 PoseI=Pose(GetPoseMean(F,step)); 0015 0016 [Hn Hi]=Absolute2RelativeJacobian(PoseN,PoseI); 0017 0018 S=R+[Hn Hi]*MarginalSigma*[Hn Hi]'; 0019 0020 ig=0.5*log(det(S)/det(R)); 0021 |