Map-aided navigation for emergency searches
Wahlstrom, J; Porto Buarque de Gusmao, P; Markham, A; et al.Trigoni, N
Date: 19 August 2019
Publisher
IEEE
Publisher DOI
Abstract
Real-time positioning of emergency personnel has
been an active research topic for many years. However, studies on
how to improve navigation accuracy by using prior information
on the idiosyncratic motion characteristics of firefighters are
scarce. This paper presents an algorithm for generating pseudo
observations of position and ...
Real-time positioning of emergency personnel has
been an active research topic for many years. However, studies on
how to improve navigation accuracy by using prior information
on the idiosyncratic motion characteristics of firefighters are
scarce. This paper presents an algorithm for generating pseudo
observations of position and orientation based on standard search
patterns used by firefighters. The iterative closest point algorithm
is used to compare walking trajectories estimated from inertial
odometry with search patterns generated from digital maps. The
resulting fitting errors are then used to integrate the pseudo
observations into a map-aided navigation filter. Specifically, we
present a sequential Monte Carlo solution where the pattern
comparison is used to both update particle weights and create
new particle samples. Experimental results involving professional
firefighters demonstrate that the proposed pseudo observations
can achieve a stable localization error of about one meter, and
offer increased robustness in the presence of map errors.
Computer Science
Faculty of Environment, Science and Economy
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