What can we learn from 38,000 rooms? Reasoning about unexplored space in indoor environments

  • Aydemir A
  • Jensfelt P
  • Folkesson J
  • 28


    Mendeley users who have this article in their library.
  • 13


    Citations of this article.


Many robotics tasks require the robot to predict what lies in the unexplored part of the environment. Although much work focuses on building autonomous robots that operate indoors, indoor environments are neither well understood nor analyzed enough in the literature. In this paper, we propose and compare two methods for predicting both the topology and the categories of rooms given a partial map. The methods are motivated by the analysis of two large annotated floor plan data sets corresponding to the buildings of the MIT and KTH campuses. In particular, utilizing graph theory, we discover that local complexity remains unchanged for growing global complexity in real-world indoor environments, a property which we exploit. In total, we analyze 197 buildings, 940 floors and over 38,000 real-world rooms. Such a large set of indoor places has not been investigated before in the previous work. We provide extensive experimental results and show the degree of transferability of spatial knowledge between two geographically distinct locations. We also contribute the KTH data set and the software tools to with it.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Alper Aydemir

  • Patric Jensfelt

  • John Folkesson

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free