get
PURPOSE 
Generic get function for filters.
SYNOPSIS
function out=get(F,field)
DESCRIPTION
Generic get function for filters.
Retives information from a filter. This basically returns the
informations common to all filters.
Possible fields to query are:
- initialState: The Gaussian with the estimation of the initial pose
of the robot.
- nSteps: Simulation steps executed by the filter.
- nStates: The number of poses in the trajectory estimated by the
filter. In general we store one pose for each step but some
filters (TRO filter) remove redundant poses. In this case
we have less estates than steps.
- dim: Dimensionality of the poses in the estimated trajectory.
- covariances: Returns a cell array with the marginal covariances for
each one of the poses stored in the filter. Note that different
filters provide different covariance estimations.
- crossCovariances: Retuns a cell array with the cross-covariances
between all the poses stored in the filter and the current
robot's pose.
- loops: Cell array with all loops closed so far.
- nLoops: The number of loops closed so far.CROSS-REFERENCE INFORMATION
This function calls:
- get Get function for robots.
- get Get function for trajectories.
- size Number of poses in a trajectory.
- GetCrossCovarianceWithPose Cross covariance of a given pose with the current one.
- GetPoseEstimation Estimation of a given pose.
- get Get function for EKF filters.
- GetCrossCovarianceWithPose Cross covariance of a given pose with the current one.
- GetPoseEstimation Estimation of a given pose.
- get Generic get function for filters.
- size Size of the state estimated in the filter
- GetCrossCovarianceWithPose Cross covariance of a given pose with the current one.
- GetPoseEstimation Estimation of a given pose.
- get Get function for TRO filters.
- get Get function for BTrees.
- get Get function for PoseData objects.
- get Get function for Gaussians.
- size Size (rows/columns) of an interval matrix.
- get Get function for poses.
- size Number of parameters of the pose.
- get Generic get for relative positioning sensors
- get Generic get for sensors
- size Number of readings stored in the Sensor.
- Trajectory Trajectory constructor.
- Experiment1a Simulated experiment.
- Experiment1b Simulated experiment.
- Experiment1c Simulated experiment.
- GetCrossCovarianceWithPose Cross covariance of a given pose with the current one.
- GetPoseEstimation Estimation of a given pose.
- P_EKF Constructor for Extended Kalman Filter for PoseSLAM.
- Update Adds a new pose to an EKF filter.
- get Get function for EKF filters.
- EKF_Prediction EKF Prediction step.
- EKF_Update EKF Update step.
- ComputeNEES Quantifies the consitency of a filter.
- GetMarginalCovariance Marginal covariance between the current pose and a previous one.
- GetPoseCovariance Marginal covariance of a given pose.
- GetPoseData Defines a PoseData objects from the information stored in the filter.
- GetPoseMean Mean estimation of a given pose.
- InitFilterPlot Initializes the plot of a filter.
- P_Filter Construtor for the base Pose SLAM filter.
- ProbDistance2PoseBelowThreshold Checks if pose 'step' is close enought to the current pose.
- Simulation Simulates a robot performing Pose SLAM.
- TreeDetectLoops Propose loops based on the distance between poses using a tree for the search.
- UpdateFilterPlot Updates the plot of a filter with a new pose.
- UpdateLoop Adds a loop to the filter.
- get Generic get function for filters.
- GetCrossCovarianceWithPose Cross covariance of a given pose with the current one.
- GetPoseCovariance Covariance estimation of a given pose.
- GetPoseEstimation Estimation of a given pose.
- GetPoseMean Mean estimation of a given pose.
- P_TRO Constructor of TRO Filters for Pose SLAM.
- Update Adds a new pose to a TRO filter.
- UpdateLoop Adds a new loop to a TRO filter.
- get Get function for TRO filters.
- TRO_Prediction Prediction Step.
- TRO_Update Filter update step.
- InsertInTree Inserts an element in a BTree.
- SearchInTree Search nearest-neighbours using a Btree
- UpdateTree Updates the information in a BTree.
- ProbDistance2PoseDataAboveThreshold p=ProbDistance2PoseDataAboveThreshold(PD,F,t,pt)
- PlotGaussian Plots a Gaussian.
- PlotPoseSequence Plots a sequence of poses.
- ContinueSimulation Continues a previous partial simulation.
- char Converts a pose to a string.
- PlotSensor Plots a sensors.
- get Generic get for relative positioning sensors
- SensorLoopCloses Checks if two sensor readigs can be properly registered.
SOURCE CODE
0001 function out=get(F,field) 0002 % Generic get function for filters. 0003 % 0004 % Retives information from a filter. This basically returns the 0005 % informations common to all filters. 0006 % 0007 % Possible fields to query are: 0008 % - initialState: The Gaussian with the estimation of the initial pose 0009 % of the robot. 0010 % - nSteps: Simulation steps executed by the filter. 0011 % - nStates: The number of poses in the trajectory estimated by the 0012 % filter. In general we store one pose for each step but some 0013 % filters (TRO filter) remove redundant poses. In this case 0014 % we have less estates than steps. 0015 % - dim: Dimensionality of the poses in the estimated trajectory. 0016 % - covariances: Returns a cell array with the marginal covariances for 0017 % each one of the poses stored in the filter. Note that different 0018 % filters provide different covariance estimations. 0019 % - crossCovariances: Retuns a cell array with the cross-covariances 0020 % between all the poses stored in the filter and the current 0021 % robot's pose. 0022 % - loops: Cell array with all loops closed so far. 0023 % - nLoops: The number of loops closed so far. 0024 0025 switch field 0026 case 'initialState' 0027 out=F.initEstimation; 0028 0029 case 'nStates' 0030 out=F.nStates; 0031 0032 case 'nSteps' 0033 out=F.nSteps; 0034 0035 case 'dim' 0036 out=F.dim; 0037 0038 case 'covariances' 0039 out=cell(1,F.nStates); 0040 for i=1:n 0041 out{i}=get(GetPoseEstimation(F,F.State2Step(F,i)),'covariance'); 0042 end 0043 0044 case 'crossCovariances' 0045 out=zeros(F.nStates*F.dim,F.dim); 0046 for i=1:n 0047 ind=(i-1)*dim+1:i*dim; 0048 out(ind)=GetCrossCovarianceWithPose(F,F.State2Step(F,i)); 0049 end 0050 0051 case 'loops' 0052 out=F.loops; 0053 0054 case 'nLoops' 0055 out=size(F.loops,2); 0056 0057 otherwise 0058 error('Unknown field in Filter get'); 0059 end