/declutter-reconstruct

Primary LanguageSmartyMIT LicenseMIT

Robust Structure Identification and Room Segmentation of Cluttered Indoor Environments from Occupancy Grid Maps

Introduction

ROSE^2 is a method for RObust StructurE identification and ROom SEgmentation (\ours ) of 2D occupancy maps, which may be cluttered and incomplete. Our method identifies the main directions of walls and is resilient to clutter and partial observations, allowing to extract a clean, abstract geometrical floor-plan-like description of the environment, which is used to segment, i.e., to identify rooms in, the original occupancy grid map. This repository should be used with the code provided by ROSE. For full details refer to the paper.

Structure of the repository

  1. The folder RESULTS contains the results as described in our paper
  2. The folder CODE contains the source code of our method
  3. The folder MAPFILES contains the maps we used in our method for evaluation

Simple working exmaple

Run the main .py file inside the CODE folder, and select the maps you want to process in the DATA folder on the prompt.

python runME.py

If you have some doubts/bugs just write to me and I'll be happy to help.