Kavraki Lab

Physical and Biological Computing

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Keywords:

Abstract:

A key subproblem in the construction of location-aware
systems is the determination of the position of a mobile
device. This article describes the design, implementation and
analysis of a system for determining position inside a building from
measured RF signal strengths of packets on an IEEE 802.11b wireless
Ethernet network. Previous approaches to location-awareness with RF
signals have been severely hampered by non-Gaussian signals, noise,
and complex correlations due to multi-path effects, interference and
absorption. The design of our system begins with the observation
that determining position from complex, noisy and non-Gaussian
signals is a wellstudied problem in the field of robotics. Using
only off-the-shelf hardware, we achieve robust position estimation
to within a meter in our experimental context and after adequate
training of our system. We can also coarsely determine our
orientation and can track our position as we move. Our results show
that we can localize a stationary device to within 1.5 meters over
80\% of the time and track a moving device to within 1 meter over
50\% of the time. Both localization and tracking run in
real-time. By applying recent advances in probabilistic inference of
position and sensor fusion from noisy signals, we show that the RF
emissions from base stations as measured by off-the-shelf wireless
Ethernet cards are sufficiently rich in information to permit a
mobile device to reliably track its location.