Slawomir Grzonka, Frederic Dijoux, Andreas Karwath, Wolfram Burgard
Mapping Indoor Environments Based on Human Activity
We present a novel approach to build approximate maps of structured
environments utilizing human motion and activity. Our approach uses data
recorded with a data suit which is equipped with several IMUs to detect
movements of a person and door opening and closing events. In our approach
we interpret the movements as motion constraints and door handling events as
landmark detections in a graph-based SLAM framework. As we cannot
distinguish between individual doors, we employ a multi-hypothesis approach
on top of the SLAM system to deal with the high data-association
uncertainty. As a result, our approach is able to accurately and robustly
recover the trajectory of the person. We additionally take advantage of the
fact that people traverse free space and that doors separate rooms to
recover the geometric structure of the environment after the graph
optimization. We evaluate our approach in several experiments carried out
with different users and in environments of different types.
Bibtex:
@InProceedings{grzonka10icra,
author = {Grzonka, Slawomir and Dijoux, Frederic and Karwath, Andreas and Burgard, Wolfram},
title = {Mapping Indoor Environments Based on Human Activity},
booktitle = {Proc. IEEE International Conference on Robotics and Automation
(ICRA)},
year = {2010},
address = {Anchorage, Alaska}
}
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