Hi Wilson,
It is my understanding that you are expecting to find an approach to process the data collected from the robot legs and form appropriate dataset to train your LSTM model. Yes, you can read in each text file and save each as a separate cell array and then add a column to the cell array to specify the pass/fail status. To do this, the textscan function in MATLAB can be used to read data from a text file.
A Sample implementation is given below,
filename = 'robot_log.txt'; % replace with the name of your text file
fileID = fopen(filename,'r');
C = textscan(fileID,...
'%f %f %f %f %f %f %f %s', ...
'HeaderLines',3,'Delimiter','\t');
fclose(fileID);
data = [C{1} C{2} C{3} C{4} C{5} C{6} C{7}];
status = C{8};
status = cellfun(@(x) strcmp(x, 'pass'), status); % convert "pass" to logical true
status = [status ~status]; % add column for "fail"
The textscan function reads in the data from the text file and store it in a cell array "C". The columns containing the accelerometer and motor speed data are then concatenated into a single array data.
You can then repeat this process to read in the data from each text file and save it as a separate cell array with the pass/fail status included. Once you have all the data stored in cell arrays, you can concatenate them into a single array if that is more convenient for subsequent processing.
