Point cloud data generation for deep learning

I want to process some point cloud data of the environment for deep learning. Due to a large amount of data and randomness, what is an efficient way to collect point cloud data? Currently, I only know to modify the .world file in Gazebo to build different environments, but obviously, this is an inefficient way.