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

Barnali Das; Gordon Dobie; Stephen Gareth Pierce

doi:10.1109/IRC.2019.00126

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

Barnali Das, Gordon Dobie, Stephen Gareth Pierce

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

4 Citations (Scopus)

97 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	624-629
Number of pages	6
ISBN (Electronic)	9781538692455
ISBN (Print)	9781538692455
DOIs	https://doi.org/10.1109/IRC.2019.00126
Publication status	Published - 26 Mar 2019
Event	The Third IEEE International Conference on Robotic Computing - Naples, Italy Duration: 25 Feb 2019 → 27 Feb 2019

Conference

Conference	The Third IEEE International Conference on Robotic Computing
Abbreviated title	IRC 2019
Country/Territory	Italy
City	Naples
Period	25/02/19 → 27/02/19

Keywords

state estimation
EKF
augmented state
telepresence
robot navigation
time delay

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10.1109/IRC.2019.00126

Das-etal-IRC2019-AS-EKF-a-delay-aware-state-estimation-technique-for-telepresenceAccepted author manuscript, 984 KB

Cite this

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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.",

keywords = "state estimation, EKF, augmented state, telepresence, robot navigation, time delay",

author = "Barnali Das and Gordon Dobie and Pierce, {Stephen Gareth}",

note = "{\textcopyright} 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.; The Third IEEE International Conference on Robotic Computing, IRC 2019 ; Conference date: 25-02-2019 Through 27-02-2019",

year = "2019",

month = mar,

day = "26",

doi = "10.1109/IRC.2019.00126",

language = "English",

isbn = "9781538692455",

pages = "624--629",

booktitle = "Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019",

publisher = "IEEE",

}

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

TY - GEN

T1 - AS-EKF

T2 - The Third IEEE International Conference on Robotic Computing

AU - Das, Barnali

AU - Dobie, Gordon

AU - Pierce, Stephen Gareth

N1 - © 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.

PY - 2019/3/26

Y1 - 2019/3/26

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.

AB - 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.

KW - state estimation

KW - EKF

KW - augmented state

KW - telepresence

KW - robot navigation

KW - time delay

U2 - 10.1109/IRC.2019.00126

DO - 10.1109/IRC.2019.00126

M3 - Conference contribution book

SN - 9781538692455

SP - 624

EP - 629

BT - Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019

PB - IEEE

CY - Piscataway, NJ

Y2 - 25 February 2019 through 27 February 2019

ER -

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

Abstract

Conference

Keywords

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