LIDAR based scan matching for indoor localization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Indoor localization has attracted more and more attention in the past few years. To achieve indoor robot navigation, it usually applies multi-on-board sensors. However, the computation loading could increase dramatically. This paper utilizes a light detection and ranging (LIDAR) device as the only sensor to detect surroundings and develops a new scan matching algorithm to realize indoor localization. To attenuate the computation effort as well as preserve localization robustness and precision, a weighted parallel ICP (WP-ICP) with interpolation is proposed. The accuracy and real time estimation capability of the proposed methods are validated through experiments. Finally, experiment comparisons are carried out and it shows that the proposed method is capable of reducing computation effort significantly and preserve localization precision simultaneously.

Original languageEnglish
Title of host publicationSII 2017 - 2017 IEEE/SICE International Symposium on System Integration
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages139-144
Number of pages6
ISBN (Electronic)9781538622636
DOIs
Publication statusPublished - 2018 Feb 1
Event2017 IEEE/SICE International Symposium on System Integration, SII 2017 - Taipei, Taiwan
Duration: 2017 Dec 112017 Dec 14

Publication series

NameSII 2017 - 2017 IEEE/SICE International Symposium on System Integration
Volume2018-January

Other

Other2017 IEEE/SICE International Symposium on System Integration, SII 2017
CountryTaiwan
CityTaipei
Period17-12-1117-12-14

Fingerprint

Sensors
Sensor
Robot Navigation
sensors
Interpolation
Navigation
Matching Algorithm
Experiments
navigation
robots
Robots
interpolation
Experiment
Interpolate
Robustness

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Instrumentation
  • Artificial Intelligence
  • Computer Science Applications
  • Engineering (miscellaneous)
  • Materials Science (miscellaneous)
  • Control and Optimization

Cite this

Peng, C. C., Wang, Y. T., & Chen, C. L. (2018). LIDAR based scan matching for indoor localization. In SII 2017 - 2017 IEEE/SICE International Symposium on System Integration (pp. 139-144). (SII 2017 - 2017 IEEE/SICE International Symposium on System Integration; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SII.2017.8279202
Peng, Chao Chung ; Wang, Yun Ting ; Chen, Chieh Li. / LIDAR based scan matching for indoor localization. SII 2017 - 2017 IEEE/SICE International Symposium on System Integration. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 139-144 (SII 2017 - 2017 IEEE/SICE International Symposium on System Integration).
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abstract = "Indoor localization has attracted more and more attention in the past few years. To achieve indoor robot navigation, it usually applies multi-on-board sensors. However, the computation loading could increase dramatically. This paper utilizes a light detection and ranging (LIDAR) device as the only sensor to detect surroundings and develops a new scan matching algorithm to realize indoor localization. To attenuate the computation effort as well as preserve localization robustness and precision, a weighted parallel ICP (WP-ICP) with interpolation is proposed. The accuracy and real time estimation capability of the proposed methods are validated through experiments. Finally, experiment comparisons are carried out and it shows that the proposed method is capable of reducing computation effort significantly and preserve localization precision simultaneously.",
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Peng, CC, Wang, YT & Chen, CL 2018, LIDAR based scan matching for indoor localization. in SII 2017 - 2017 IEEE/SICE International Symposium on System Integration. SII 2017 - 2017 IEEE/SICE International Symposium on System Integration, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 139-144, 2017 IEEE/SICE International Symposium on System Integration, SII 2017, Taipei, Taiwan, 17-12-11. https://doi.org/10.1109/SII.2017.8279202

LIDAR based scan matching for indoor localization. / Peng, Chao Chung; Wang, Yun Ting; Chen, Chieh Li.

SII 2017 - 2017 IEEE/SICE International Symposium on System Integration. Institute of Electrical and Electronics Engineers Inc., 2018. p. 139-144 (SII 2017 - 2017 IEEE/SICE International Symposium on System Integration; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - LIDAR based scan matching for indoor localization

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N2 - Indoor localization has attracted more and more attention in the past few years. To achieve indoor robot navigation, it usually applies multi-on-board sensors. However, the computation loading could increase dramatically. This paper utilizes a light detection and ranging (LIDAR) device as the only sensor to detect surroundings and develops a new scan matching algorithm to realize indoor localization. To attenuate the computation effort as well as preserve localization robustness and precision, a weighted parallel ICP (WP-ICP) with interpolation is proposed. The accuracy and real time estimation capability of the proposed methods are validated through experiments. Finally, experiment comparisons are carried out and it shows that the proposed method is capable of reducing computation effort significantly and preserve localization precision simultaneously.

AB - Indoor localization has attracted more and more attention in the past few years. To achieve indoor robot navigation, it usually applies multi-on-board sensors. However, the computation loading could increase dramatically. This paper utilizes a light detection and ranging (LIDAR) device as the only sensor to detect surroundings and develops a new scan matching algorithm to realize indoor localization. To attenuate the computation effort as well as preserve localization robustness and precision, a weighted parallel ICP (WP-ICP) with interpolation is proposed. The accuracy and real time estimation capability of the proposed methods are validated through experiments. Finally, experiment comparisons are carried out and it shows that the proposed method is capable of reducing computation effort significantly and preserve localization precision simultaneously.

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Peng CC, Wang YT, Chen CL. LIDAR based scan matching for indoor localization. In SII 2017 - 2017 IEEE/SICE International Symposium on System Integration. Institute of Electrical and Electronics Engineers Inc. 2018. p. 139-144. (SII 2017 - 2017 IEEE/SICE International Symposium on System Integration). https://doi.org/10.1109/SII.2017.8279202