53 lines
2.4 KiB
Matlab
53 lines
2.4 KiB
Matlab
function [robot] = TX40_uncoupled(options, varargin)
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[robot] = TX40(options);
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robot.name = 'TX40_uncoupled';
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if isfield(robot,'symbolicParameters')
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robot.symbolicParameters.Xhi = robot.symbolicParameters.Xhi(1:end-2);
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robot.symbolicParameters.Xhi_aug = robot.symbolicParameters.Xhi_aug(1:end-2);
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end
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robot.numericalParameters.Xhi = robot.numericalParameters.Xhi(1:end-2);
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robot.numericalParameters.numParam(end) = robot.numericalParameters.numParam(end)-2;
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switch options.noiseLevel
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case 'oldNoise'
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robot.numericalParameters.sd_q = [0.057e-3; 0.057e-3; 0.122e-3; 0.114e-3; 0.122e-3; 0.172e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 5e-2*ones(robot.nbDOF,1); % Noise standard deviation
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case 'lowPositionNoise'
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% Standard
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robot.numericalParameters.sd_q = [1e-4; 1e-4; 1e-4; 1e-4; 1e-4; 1e-4].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 5*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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case 'standardNoise'
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% Standard
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robot.numericalParameters.sd_q = [1e-3; 1e-3; 1e-3; 1e-3; 1e-3; 1e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 5*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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case 'highTorqueNoise'
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% High torque noise
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robot.numericalParameters.sd_q = [1e-3; 1e-3; 1e-3; 1e-3; 1e-3; 1e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 10*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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case 'highPositionNoise'
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% High position noise
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robot.numericalParameters.sd_q = 10*[1e-3; 1e-3; 1e-3; 1e-3; 1e-3; 1e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 5*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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case 'highPositionTorqueNoise'
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% High torque and position noise
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robot.numericalParameters.sd_q = 10*[1e-3; 1e-3; 1e-3; 1e-3; 1e-3; 1e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 10*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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otherwise
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% Standard
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robot.numericalParameters.sd_q = [1e-3; 1e-3; 1e-3; 1e-3; 1e-3; 1e-3].*pi/180; % Noise standard deviation
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robot.numericalParameters.sd_tau = 5*[1e-2; 1e-2; 1e-2; 1e-2; 1e-2; 1e-2]; % Noise standard deviation
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end
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end
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