  Inferring walls configuration of indoor environment could help robot
"understand" the environment better. This allows the robot to execute a task
that involves inter-room navigation, such as picking an object in the kitchen.
In this paper, we present a method to inferring walls configuration from a
moving RGB-D sensor. Our goal is to combine a simple wall configuration model
and fast wall detection method in order to get a system that works online, is
real-time, and does not need a Manhattan World assumption. We tested our
preliminary work, i.e. wall detection and measurement from moving RGB-D sensor,
with MIT Stata Center Dataset. The performance of our method is reported in
terms of accuracy and speed of execution.
