Novel sonar salient feature structure for extended kalman filter-based simultaneous localization and mapping of mobile robots

Se Jin Lee, Dong Woo Cho, Jae-Bok Song

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Not all line or point features capable of being extracted by sonar sensors from a cluttered home environment are useful for simultaneous localization and mapping (SLAM) of a mobile robot. This is due to unfavorable conditions such as environmental ambiguity and sonar measurement uncertainty. We present a novel sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The key concept is to extract circle feature clouds on salient convex objects by sonar data association called convex saliency circling. The centroid of each circle cloud, called a sonar salient feature, is used as a natural landmark for EKF-based SLAM. By investigating the environmental inherent feature locality, cylindrical objects are augmented conveniently at the weak SLAM-able area as a natural supplementary saliency to achieve consistent SLAM performance. Experimental results demonstrate the validity and robustness of the proposed sonar salient feature structure for EKF-based SLAM.

Original languageEnglish
Pages (from-to)1055-1074
Number of pages20
JournalAdvanced Robotics
Volume26
Issue number8-9
DOIs
Publication statusPublished - 2012 May 1

Fingerprint

Sonar
Extended Kalman filters
Mobile robots
Sensors

Keywords

  • feature maps
  • home navigation
  • simultaneous localization and mapping
  • Sonars
  • wheeled robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Hardware and Architecture
  • Software

Cite this

Novel sonar salient feature structure for extended kalman filter-based simultaneous localization and mapping of mobile robots. / Lee, Se Jin; Cho, Dong Woo; Song, Jae-Bok.

In: Advanced Robotics, Vol. 26, No. 8-9, 01.05.2012, p. 1055-1074.

Research output: Contribution to journalArticle

@article{3299a0ddad3c4a0d979f20b581a4a0e9,
title = "Novel sonar salient feature structure for extended kalman filter-based simultaneous localization and mapping of mobile robots",
abstract = "Not all line or point features capable of being extracted by sonar sensors from a cluttered home environment are useful for simultaneous localization and mapping (SLAM) of a mobile robot. This is due to unfavorable conditions such as environmental ambiguity and sonar measurement uncertainty. We present a novel sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The key concept is to extract circle feature clouds on salient convex objects by sonar data association called convex saliency circling. The centroid of each circle cloud, called a sonar salient feature, is used as a natural landmark for EKF-based SLAM. By investigating the environmental inherent feature locality, cylindrical objects are augmented conveniently at the weak SLAM-able area as a natural supplementary saliency to achieve consistent SLAM performance. Experimental results demonstrate the validity and robustness of the proposed sonar salient feature structure for EKF-based SLAM.",
keywords = "feature maps, home navigation, simultaneous localization and mapping, Sonars, wheeled robots",
author = "Lee, {Se Jin} and Cho, {Dong Woo} and Jae-Bok Song",
year = "2012",
month = "5",
day = "1",
doi = "10.1163/156855312X633093",
language = "English",
volume = "26",
pages = "1055--1074",
journal = "Advanced Robotics",
issn = "0169-1864",
publisher = "Taylor and Francis Ltd.",
number = "8-9",

}

TY - JOUR

T1 - Novel sonar salient feature structure for extended kalman filter-based simultaneous localization and mapping of mobile robots

AU - Lee, Se Jin

AU - Cho, Dong Woo

AU - Song, Jae-Bok

PY - 2012/5/1

Y1 - 2012/5/1

N2 - Not all line or point features capable of being extracted by sonar sensors from a cluttered home environment are useful for simultaneous localization and mapping (SLAM) of a mobile robot. This is due to unfavorable conditions such as environmental ambiguity and sonar measurement uncertainty. We present a novel sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The key concept is to extract circle feature clouds on salient convex objects by sonar data association called convex saliency circling. The centroid of each circle cloud, called a sonar salient feature, is used as a natural landmark for EKF-based SLAM. By investigating the environmental inherent feature locality, cylindrical objects are augmented conveniently at the weak SLAM-able area as a natural supplementary saliency to achieve consistent SLAM performance. Experimental results demonstrate the validity and robustness of the proposed sonar salient feature structure for EKF-based SLAM.

AB - Not all line or point features capable of being extracted by sonar sensors from a cluttered home environment are useful for simultaneous localization and mapping (SLAM) of a mobile robot. This is due to unfavorable conditions such as environmental ambiguity and sonar measurement uncertainty. We present a novel sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The key concept is to extract circle feature clouds on salient convex objects by sonar data association called convex saliency circling. The centroid of each circle cloud, called a sonar salient feature, is used as a natural landmark for EKF-based SLAM. By investigating the environmental inherent feature locality, cylindrical objects are augmented conveniently at the weak SLAM-able area as a natural supplementary saliency to achieve consistent SLAM performance. Experimental results demonstrate the validity and robustness of the proposed sonar salient feature structure for EKF-based SLAM.

KW - feature maps

KW - home navigation

KW - simultaneous localization and mapping

KW - Sonars

KW - wheeled robots

UR - http://www.scopus.com/inward/record.url?scp=84865693453&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865693453&partnerID=8YFLogxK

U2 - 10.1163/156855312X633093

DO - 10.1163/156855312X633093

M3 - Article

AN - SCOPUS:84865693453

VL - 26

SP - 1055

EP - 1074

JO - Advanced Robotics

JF - Advanced Robotics

SN - 0169-1864

IS - 8-9

ER -