What does "Two-Stage Learning" mean?
Table of Contents
Two-stage learning is a method used to improve how computers or robots find their way to a specific object. This process involves two main steps: searching for the object and then navigating to it.
Searching Stage
In the first stage, the computer looks for the object in a larger area. It uses both pictures and depth information to gather details about the environment. This helps the computer become familiar with what’s around it before it starts to move.
Navigating Stage
Once the computer knows where the object is, it enters the second stage. Here, it focuses on choosing the best path to reach the object, avoiding obstacles along the way. The computer remembers where things are to prevent bumps and getting stuck.
Benefits
By separating these two stages, the computer can work more efficiently. It becomes better at reaching the destination without unnecessary delays or mistakes. This method shows improvement over older approaches that did not take these differences into account.