dc.contributor.author | Wahlstrom, J | |
dc.contributor.author | Porto Buarque de Gusmao, P | |
dc.contributor.author | Markham, A | |
dc.contributor.author | Trigoni, N | |
dc.date.accessioned | 2020-07-23T13:37:10Z | |
dc.date.issued | 2019-08-19 | |
dc.description.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 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. | en_GB |
dc.identifier.citation | 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini Island, Greece, 29 May 2019 - 31 May 2019 | en_GB |
dc.identifier.doi | 10.1109/dcoss.2019.00027 | |
dc.identifier.uri | http://hdl.handle.net/10871/122106 | |
dc.language.iso | en | en_GB |
dc.publisher | IEEE | en_GB |
dc.rights | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be
obtained for all other uses, in any current or future media, including
reprinting/republishing this material for advertising or promotional purposes, creating new
collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted
component of this work in other works. | en_GB |
dc.title | Map-aided navigation for emergency searches | en_GB |
dc.type | Conference proceedings | en_GB |
dc.date.available | 2020-07-23T13:37:10Z | |
dc.identifier.isbn | 978-1-7281-0571-0 | |
dc.identifier.issn | 2325-2944 | |
dc.description | This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2019 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2020-07-23T13:35:06Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-07-23T13:37:20Z | |
refterms.panel | B | en_GB |