I know that Occupancy Grid Mapping requires the assumption that the robots' pose is always known when generating a map. However, I also know that in reality, position and orientation usually treated as uncertain in practical applications. Assuming that my target mapping environment is inside a home, is there a way I can overcome inherent robot pose uncertainty in a real world application of Occupancy Grid Mapping without resorting to implementing a SLAM? That is, what is a low-cost way to increase the certainty about my pose?
Or is Occupancy Grid Mapping only useful in theory and not in practice?
It is clear to me, from the responses given, that occupancy grid mapping is just one possible way to represent a map, not a method in and of itself. The heart of what I really want to know is: Can mapping be done without also solving the localization problem at the same time (i.e. SLAM) in real life applications?