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?
Update:
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?