N = ccl_learna_pred_proj_lambda (model, q, Iu) Prediction of the projection matrix Our model predicts the constraint parameters. this function is used to reconstuct the projection matrix from constraint paramters. Input: model Parametric model parameters q Joint state data Iu Identity matrix Output: N Null space projection
0001 function N = ccl_learna_pred_proj_lambda (q, model, J, Iu) 0002 % N = ccl_learna_pred_proj_lambda (model, q, Iu) 0003 % Prediction of the projection matrix 0004 % Our model predicts the constraint parameters. this function is used to 0005 % reconstuct the projection matrix from constraint paramters. 0006 % 0007 % Input: 0008 % model Parametric model parameters 0009 % q Joint state data 0010 % Iu Identity matrix 0011 % 0012 % Output: 0013 % N Null space projection 0014 0015 Rn = Iu ; % Initial rotation matrix 0016 Lambda = zeros(model.dim_k, model.dim_r) ; % Initial selection matrix 0017 0018 for k = 1:model.dim_k 0019 theta = [pi/2 * ones(1,k-1) , (model.w{k} * model.phi(q) )' ] ; 0020 alpha = ccl_math_uvec(theta) ; % the kth alpha_0 0021 Lambda(k,:) = alpha * Rn ; % rotate alpha_0 to get the kth constraint 0022 Rn = ccl_math_rotmat (theta, Rn, model, k) ; % update rotation matrix for (k+1) 0023 end 0024 A = Lambda * J(q) ; 0025 N = eye(model.dim_u) - pinv(A)*A ; 0026 end