The resulting data is stored in a temporary storage (the PC RAM in my case). For example if I have to make a mathematical operation on the raw data, say a subtraction or even a sine. The idea is to build a specific dataset out of the raw data. Prepare and preprocess the data to be learnt.To ease the learning process using the DeMIMOI models, I decided to proceed in 4 steps : I’m used to neural networks, they are powerful non linear models, so I decided to implement a framework that will help me make the model learn the data. I quickly found that the data won’t be linear, so that I’ll need a non linear model to map the data. I started by trying to analyze the data I gathered to determine its properties. To make this prediction, the model inputs will be the object position on each image and the current arm joint angles. Now the goal is to build a model that will predict the arm joint angles that will place the arm at the location of the object. Arm joint angles at the object location : (alphaT, betaT, thetaT, gammaT).Arm joint angles where the object has been seen : (alphaI, betaI, thetaI, gammaI).Position of object on the right image (xR, yR).Position of object on the left image (xL, yL).database record), I recorded these values we have this : The data contains the detected object coordinates on the left and right image, the robot arm joint angles where it detected the object and the same variables but when the arm is placed manually on the object.
At the previous step I collected data using my robot arm and the webcams I installed on it.
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