Commit 15c9aed6 authored by Martin Karlsson's avatar Martin Karlsson
Browse files

läget mannen :)

parent 70c31d32
...@@ -17,9 +17,6 @@ if isempty(fs) ...@@ -17,9 +17,6 @@ if isempty(fs)
end end
p = bass.Audio(); p = bass.Audio();
pause(0.1)
lastIndex = p.Audio.lastFrameIndex; lastIndex = p.Audio.lastFrameIndex;
diffIndex = lastIndex - lastLastIndex; diffIndex = lastIndex - lastLastIndex;
tempLeft = cell2mat(p.Audio.left); tempLeft = cell2mat(p.Audio.left);
...@@ -37,4 +34,5 @@ signal = [tempLeft, tempRight]; ...@@ -37,4 +34,5 @@ signal = [tempLeft, tempRight];
%bass.Stop(); %bass.Stop();
end end
\ No newline at end of file
...@@ -5,4 +5,4 @@ global bass ...@@ -5,4 +5,4 @@ global bass
addpath(genpath('~/openrobots/lib/matlab/')); addpath(genpath('~/openrobots/lib/matlab/'));
client = genomix.client('turtlebot1-wifi:8080'); client = genomix.client('turtlebot1-wifi:8080');
bass = client.load('bass'); bass = client.load('bass');
bass.Acquire('-a',24414,2048,80); bass.Acquire('-a',24414,2048,2);
\ No newline at end of file \ No newline at end of file
...@@ -11,7 +11,7 @@ dt = chunks/fs; ...@@ -11,7 +11,7 @@ dt = chunks/fs;
%% Setup objects %% Setup objects
% Initialize localization models using braodband and subband settings % Initialize localization models using braodband and subband settings
dObj = dataObject([],fsHz,10,2); dObj = dataObject([],fs,10,2);
% Settings for subband approach % Settings for subband approach
par_sub = genParStruct('cc_bBroadband',0,'cc_wSizeSec',winSec,... par_sub = genParStruct('cc_bBroadband',0,'cc_wSizeSec',winSec,...
...@@ -50,7 +50,7 @@ addpath('./ekfukf-toolbox'); ...@@ -50,7 +50,7 @@ addpath('./ekfukf-toolbox');
figure(1) figure(1)
N = 100; % The number of steps to run this stuff. N = 1; % The number of steps to run this stuff.
% Initialize posterior mean and covariance % Initialize posterior mean and covariance
posteriorMean = zeros(size(A, 1), N); posteriorMean = zeros(size(A, 1), N);
...@@ -80,7 +80,7 @@ for l = 1:N ...@@ -80,7 +80,7 @@ for l = 1:N
posteriorMean(:, l) = x; posteriorMean(:, l) = x;
posteriorCovariance(:, :, l) = P; posteriorCovariance(:, :, l) = P;
pause(max(,0)) %pause(max0))
t_old = t_new; t_old = t_new;
end end
......
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