@ptrblck If we set aside running the observations through a NN, for the moment, what sort of data-structure should I use to treat the image, pose and sonar senor reading as a single sample, using numpy?
The word ‘Tensor’ comes to mind, since at one data point, you have multiple quantities being represented: image (84x84x1), pose (6x1) + sensor reading (1x1).
All but the last dimension of these three quantities match.
How can I create a ‘Tensor’ using numpy, as a first step? This is so that I treat observations as tensors within the OpenAI Gym environment.