AS-EKF: a delay aware state estimation technique for telepresence robot navigation

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

Abstract

State estimation in dynamical telepresence systemsis very important in real-world applications as the true state of the robot is unspecified and sensors provide only a sequence of noisy measurements. In this research, we proposed a new technique of state estimation using delayed sensor measurements of a Telepresence robot for real-time navigation. An Augmented State Extended Kalman Filter (AS-EKF) is introduced to estimate the true position of the robot. The proposed algorithm was successfully tested in a real-environment experimental frameworkusing a state-of-the-art differential-drive telepresence robot. Our results show improvements of an average of more than 34% when compared to traditional EKF.
LanguageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages624-629
Number of pages6
ISBN (Electronic)9781538692455
ISBN (Print)9781538692455
DOIs
Publication statusPublished - 26 Mar 2019
EventThe Third IEEE International Conference on Robotic Computing - Naples, Italy
Duration: 25 Feb 201927 Feb 2019

Conference

ConferenceThe Third IEEE International Conference on Robotic Computing
Abbreviated titleIRC 2019
CountryItaly
CityNaples
Period25/02/1927/02/19

Fingerprint

Extended Kalman filters
State estimation
Navigation
Robots
Sensors

Keywords

  • state estimation
  • EKF
  • augmented state
  • telepresence
  • robot navigation
  • time delay

Cite this

Das, B., Dobie, G., & Pierce, S. G. (2019). AS-EKF: a delay aware state estimation technique for telepresence robot navigation. In Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019 (pp. 624-629). [8675655] Piscataway, NJ: IEEE. https://doi.org/10.1109/IRC.2019.00126
Das, Barnali ; Dobie, Gordon ; Pierce, Stephen Gareth. / AS-EKF : a delay aware state estimation technique for telepresence robot navigation. Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019. Piscataway, NJ : IEEE, 2019. pp. 624-629
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title = "AS-EKF: a delay aware state estimation technique for telepresence robot navigation",
abstract = "State estimation in dynamical telepresence systemsis very important in real-world applications as the true state of the robot is unspecified and sensors provide only a sequence of noisy measurements. In this research, we proposed a new technique of state estimation using delayed sensor measurements of a Telepresence robot for real-time navigation. An Augmented State Extended Kalman Filter (AS-EKF) is introduced to estimate the true position of the robot. The proposed algorithm was successfully tested in a real-environment experimental frameworkusing a state-of-the-art differential-drive telepresence robot. Our results show improvements of an average of more than 34{\%} when compared to traditional EKF.",
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note = "{\circledC} 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.",
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Das, B, Dobie, G & Pierce, SG 2019, AS-EKF: a delay aware state estimation technique for telepresence robot navigation. in Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019., 8675655, IEEE, Piscataway, NJ, pp. 624-629, The Third IEEE International Conference on Robotic Computing, Naples, Italy, 25/02/19. https://doi.org/10.1109/IRC.2019.00126

AS-EKF : a delay aware state estimation technique for telepresence robot navigation. / Das, Barnali; Dobie, Gordon; Pierce, Stephen Gareth.

Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019. Piscataway, NJ : IEEE, 2019. p. 624-629 8675655.

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

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N2 - State estimation in dynamical telepresence systemsis very important in real-world applications as the true state of the robot is unspecified and sensors provide only a sequence of noisy measurements. In this research, we proposed a new technique of state estimation using delayed sensor measurements of a Telepresence robot for real-time navigation. An Augmented State Extended Kalman Filter (AS-EKF) is introduced to estimate the true position of the robot. The proposed algorithm was successfully tested in a real-environment experimental frameworkusing a state-of-the-art differential-drive telepresence robot. Our results show improvements of an average of more than 34% when compared to traditional EKF.

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Das B, Dobie G, Pierce SG. AS-EKF: a delay aware state estimation technique for telepresence robot navigation. In Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019. Piscataway, NJ: IEEE. 2019. p. 624-629. 8675655 https://doi.org/10.1109/IRC.2019.00126