12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Moved to CitySLAM

release/4.3a0
Frank Dellaert 2012-07-28 17:04:20 +00:00
parent b32931f879
commit 25ffc8adda
2 changed files with 0 additions and 88 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
matlab/examples/Pose2SLAMExample_graph1.m
View File

@ -1,36 +0,0 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% GTSAM Copyright 2010, Georgia Tech Research Corporation,
% Atlanta, Georgia 30332-0415
% All Rights Reserved
% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
%
% See LICENSE for the license information
%
% @brief Read graph from file and perform GraphSLAM
% @author Frank Dellaert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Initialize graph, initial estimate, and odometry noise
import gtsam.*
model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 1*pi/180]);
maxID=0;
addNoise=false;
smart=true;
[graph,initial]=load2D('Data/w10000-odom.graph',model,maxID,addNoise,smart);
%% Add a Gaussian prior on pose x_1
priorMean = Pose2(0.0, 0.0, 0.0); % prior mean is at origin
priorNoise = noiseModel.Diagonal.Sigmas([0.01; 0.01; 0.01]);
graph.addPosePrior(0, priorMean, priorNoise); % add directly to graph
%% Plot Initial Estimate
figure(1);clf
P=initial.poses;
plot(P(:,1),P(:,2),'r-'); axis equal
%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
tic
result = graph.optimize(initial,1);
toc
P=result.poses;
hold on; plot(P(:,1),P(:,2),'b-')

52
matlab/examples/Pose2SLAMExample_graph2.m
View File

@ -1,52 +0,0 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% GTSAM Copyright 2010, Georgia Tech Research Corporation,
% Atlanta, Georgia 30332-0415
% All Rights Reserved
% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
%
% See LICENSE for the license information
%
% @brief Read graph from file and perform GraphSLAM
% @author Frank Dellaert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
import gtsam.*
maxID=0;
addNoise=false;
smart=true;
priorMean = Pose2(0.0, 0.0, 0.0); % prior mean is at origin
priorNoise = noiseModel.Diagonal.Sigmas([0.01; 0.01; 0.01]);
%% Create graph, disregarding translation measurements by setting sigma high
model = noiseModel.Diagonal.Sigmas([100000; 100000; 1*pi/180]);
[graph,initial]=load2D('Data/w10000-odom.graph',model,maxID,addNoise,smart);
%% Add a Gaussian prior on pose x_1
graph.addPosePrior(0, priorMean, priorNoise); % add directly to graph
%% Plot Initial Estimate
figure(1);clf
P=initial.poses;
plot(P(:,1),P(:,2),'r-'); axis equal
%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
tic
result1 = graph.optimize(initial,1);
toc
P=result1.poses;
hold on; plot(P(:,1),P(:,2),'g-')
%% Read again, with correct noise now...
model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 1*pi/180]);
graph=load2D('Data/w10000-odom.graph',model,maxID,addNoise,smart);
%% Add a Gaussian prior on pose x_1
graph.addPosePrior(0, priorMean, priorNoise); % add directly to graph
%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
tic
result2 = graph.optimize(result1,1);
toc
P=result2.poses;
hold on; plot(P(:,1),P(:,2),'b-')