M. Bennewitz, W. Burgard, S. Thrun
Using EM to Learn Motion Behaviors of Persons with Mobile
Robots
In Proc. of the IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), 2002.
Abstract
We propose a method for learning models of people's motion behaviors
in indoor environments. As people move through their environments,
they do not move randomly. Instead, they often engage in typical
motion patterns, related to specific locations that they might be
interested in approaching and specific trajectories that they might
follow in doing so. Knowledge about such patterns may enable a
mobile robot to develop improved people following and obstacle
avoidance skills. This paper proposes an algorithm that learns
collections of typical trajectories that characterize a person's
motion patterns. Data, recorded by mobile robots equipped with
laser-range finders, is clustered into different types of motion
using the popular expectation maximization algorithm, while
simultaneously learning multiple motion patterns. Experimental
results, obtained using data collected in a domestic residence and
in an office building, illustrate that highly predictive models of
human motion patterns can be learned.
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Bibtex
@InProceedings{Bennewitz02Using,
author = {Bennewitz, M. and Burgard, W.
and Thrun, S.},
title = {Using {EM} to Learn Motion Behaviors of Persons with Mobile Robots},
booktitle = {Proc.~of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year = {2002},
}