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Localisation, tracking, and navigation support for pedestrians in uninstrumented and unknown environments

Research output: ThesisDoctoral Thesis

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Localisation, tracking, and navigation support for pedestrians in uninstrumented and unknown environments. / Fischer, Carl.
Lancaster: Lancaster University, 2012. 264 p.

Research output: ThesisDoctoral Thesis

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APA

Fischer, C. (2012). Localisation, tracking, and navigation support for pedestrians in uninstrumented and unknown environments. [Doctoral Thesis, Lancaster University]. Lancaster University.

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Bibtex

@phdthesis{f6513860e90549e8bf8096245b4dbb73,
title = "Localisation, tracking, and navigation support for pedestrians in uninstrumented and unknown environments",
abstract = "Research into localisation and tracking of pedestrians is a growing area, but developed techniques have tended to be infrastructure-based or to rely on accessto prior information such as floorplans and maps. There are situations, such assearch and rescue missions, where more robust and versatile self-contained localisation systems are desirable. To our knowledge, this a relatively unexplored area of research. Relative localisation, involving only objects in the vicinity of the target being tracked, offers a partial solution by not requiring any infrastructure. We demonstrate and discuss some techniques based on this approach, and develop an algorithm suitable for tracking highly mobile sensor networks. We also highlight its limitations and look for complementary oolutions. Pedestrian dead reckoning (PDR) based on foot-mounted inertial sensors is a promising method which we describe in detail, including its inherent flaws. We combine the dead reckoning and sensor node techniques to perform simultaneous localisation and mapping (SLAM) for pedestrians in indoor environments. Finally, we include our SLAM algorithm in a complete navigation solution which we evaluate in a virtual environment.This study allows us to offer insight into problems and opportunities offered by these technologies and their application in the field of pedestrian navigation in uninstrumented and unknown environments. We describe the potential offered by tracking and navigation once they are no longer dependent on infrastructure, predeployment, or prior knowledge of an area.",
keywords = "tracking, pedestrian navigation, inertial sensing, wearable sensors, emergency response, indoor localisation, dead reckoning",
author = "Carl Fischer",
year = "2012",
month = sep,
language = "English",
publisher = "Lancaster University",
school = "Lancaster University",

}

RIS

TY - BOOK

T1 - Localisation, tracking, and navigation support for pedestrians in uninstrumented and unknown environments

AU - Fischer, Carl

PY - 2012/9

Y1 - 2012/9

N2 - Research into localisation and tracking of pedestrians is a growing area, but developed techniques have tended to be infrastructure-based or to rely on accessto prior information such as floorplans and maps. There are situations, such assearch and rescue missions, where more robust and versatile self-contained localisation systems are desirable. To our knowledge, this a relatively unexplored area of research. Relative localisation, involving only objects in the vicinity of the target being tracked, offers a partial solution by not requiring any infrastructure. We demonstrate and discuss some techniques based on this approach, and develop an algorithm suitable for tracking highly mobile sensor networks. We also highlight its limitations and look for complementary oolutions. Pedestrian dead reckoning (PDR) based on foot-mounted inertial sensors is a promising method which we describe in detail, including its inherent flaws. We combine the dead reckoning and sensor node techniques to perform simultaneous localisation and mapping (SLAM) for pedestrians in indoor environments. Finally, we include our SLAM algorithm in a complete navigation solution which we evaluate in a virtual environment.This study allows us to offer insight into problems and opportunities offered by these technologies and their application in the field of pedestrian navigation in uninstrumented and unknown environments. We describe the potential offered by tracking and navigation once they are no longer dependent on infrastructure, predeployment, or prior knowledge of an area.

AB - Research into localisation and tracking of pedestrians is a growing area, but developed techniques have tended to be infrastructure-based or to rely on accessto prior information such as floorplans and maps. There are situations, such assearch and rescue missions, where more robust and versatile self-contained localisation systems are desirable. To our knowledge, this a relatively unexplored area of research. Relative localisation, involving only objects in the vicinity of the target being tracked, offers a partial solution by not requiring any infrastructure. We demonstrate and discuss some techniques based on this approach, and develop an algorithm suitable for tracking highly mobile sensor networks. We also highlight its limitations and look for complementary oolutions. Pedestrian dead reckoning (PDR) based on foot-mounted inertial sensors is a promising method which we describe in detail, including its inherent flaws. We combine the dead reckoning and sensor node techniques to perform simultaneous localisation and mapping (SLAM) for pedestrians in indoor environments. Finally, we include our SLAM algorithm in a complete navigation solution which we evaluate in a virtual environment.This study allows us to offer insight into problems and opportunities offered by these technologies and their application in the field of pedestrian navigation in uninstrumented and unknown environments. We describe the potential offered by tracking and navigation once they are no longer dependent on infrastructure, predeployment, or prior knowledge of an area.

KW - tracking

KW - pedestrian navigation

KW - inertial sensing

KW - wearable sensors

KW - emergency response

KW - indoor localisation

KW - dead reckoning

M3 - Doctoral Thesis

PB - Lancaster University

CY - Lancaster

ER -