Robust sensor cloud localization from range measurements

G. Dubbelman; E. Duisterwinkel; L. Demi; E. Talnishnikh; H.J. Wörtche; J.W. Bergmanns

doi:10.1109/iros.2014.6943099

Robust sensor cloud localization from range measurements

G. Dubbelman
, E. Duisterwinkel
, L. Demi
, E. Talnishnikh
, H.J. Wörtche
, J.W. Bergmanns

Sensors and Smart Systems

Research output: Chapter in Book/Report/Conference proceeding › Contribution to conference proceeding › Academic › peer-review

Abstract

This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.

Original language	English
Title of host publication	IEEE International Conference on Intelligent Robots and Systems
Pages	3820-3827
Number of pages	8
DOIs	https://doi.org/10.1109/iros.2014.6943099
Publication status	Published - 31 Oct 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 03 Good Health and Well-being
SDG 09 Industry, Innovation, and Infrastructure

Keywords

robot sensing systems
ultrasonic imaging

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

Healthy Ageing

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

Artificial Intelligence
Cyberfysical systems

Publinova themes

ICT and Media
Health
Technology

Access to Document

10.1109/iros.2014.6943099

Cite this

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title = "Robust sensor cloud localization from range measurements",

abstract = "This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.",

keywords = "robot sensing systems, ultrasonic imaging",

author = "G. Dubbelman and E. Duisterwinkel and L. Demi and E. Talnishnikh and H.J. W{\"o}rtche and J.W. Bergmanns",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

year = "2014",

month = oct,

day = "31",

doi = "10.1109/iros.2014.6943099",

language = "English",

isbn = "9781479969340",

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AU - Dubbelman, G.

AU - Duisterwinkel, E.

AU - Demi, L.

AU - Talnishnikh, E.

AU - Wörtche, H.J.

AU - Bergmanns, J.W.

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2014/10/31

Y1 - 2014/10/31

N2 - This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.

AB - This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.

KW - robot sensing systems

KW - ultrasonic imaging

U2 - 10.1109/iros.2014.6943099

DO - 10.1109/iros.2014.6943099

M3 - Contribution to conference proceeding

SN - 9781479969340

SP - 3820

EP - 3827

BT - IEEE International Conference on Intelligent Robots and Systems

ER -

Robust sensor cloud localization from range measurements

Abstract

UN SDGs

Keywords

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

Publinova themes

Access to Document

Fingerprint

Cite this