Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement

Emile Mackute; Balint Thamo; Kevin Dhaliwal; Mohsen Khadem

doi:10.1109/IROS47612.2022.9982174

Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement

Emile Mackute, Balint Thamo, Kevin Dhaliwal, Mohsen Khadem

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

Abstract / Description of output

Accurate shape estimation of concentric tube robots (CTRs) using mathematical models remains a challenge, reinforcing the need to develop techniques for accurate and real-time shape sensing of CTRs. In this paper, we develop a fusion algorithm that predicts the robot's shape by combining a mathematical model of the CTR with a measurement of the Cartesian coordinates of the robot's tip using an electro-magnetic sensor. We experimentally validated our method in static and dynamic scenarios with and without external loading. Results demonstrated that the fusion algorithm improves the error of model-based shape prediction by an average of 44.3%, corresponding to 2.43% of the robot's arc length. Furthermore, we demonstrate that our method can be used in real-time to simultaneously track the robot's tip position and predict its shape.

Original language	English
Title of host publication	2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Publisher	Institute of Electrical and Electronics Engineers
Pages	3972-3978
Number of pages	7
ISBN (Electronic)	978-1-6654-7927-1
ISBN (Print)	978-1-6654-7928-8
DOIs	https://doi.org/10.1109/IROS47612.2022.9982174
Publication status	Published - 26 Dec 2022
Event	IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022): IROS Kyoto 2022 - Japan, Kyoto, Japan Duration: 23 Oct 2022 → 27 Oct 2022 https://iros2022.org/

Publication series

Name
Publisher	IEEE
ISSN (Print)	2153-0858
ISSN (Electronic)	2153-0866

Conference

Conference	IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
Country/Territory	Japan
City	Kyoto
Period	23/10/22 → 27/10/22
Internet address	https://iros2022.org/

Access to Document

10.1109/IROS47612.2022.9982174Licence: All Rights Reserved

Shape Estimation_MACKUTE_DOA30062022_AFV_CC-BYAccepted author manuscript, 4.13 MBLicence: Creative Commons: Attribution (CC-BY)

https://ieeexplore.ieee.org/document/9982174Licence: All Rights Reserved

A Cyber-Physical System for Unified Diagnosis and Treatment of Lung Diseases
Khadem, M. & Ramamoorthy, R.
MRC
1/05/20 → 30/04/24
Project: Research

Cite this

@inproceedings{4107046336254372816e5423f5b8fdd7,

title = "Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement",

abstract = "Accurate shape estimation of concentric tube robots (CTRs) using mathematical models remains a challenge, reinforcing the need to develop techniques for accurate and real-time shape sensing of CTRs. In this paper, we develop a fusion algorithm that predicts the robot's shape by combining a mathematical model of the CTR with a measurement of the Cartesian coordinates of the robot's tip using an electro-magnetic sensor. We experimentally validated our method in static and dynamic scenarios with and without external loading. Results demonstrated that the fusion algorithm improves the error of model-based shape prediction by an average of 44.3%, corresponding to 2.43% of the robot's arc length. Furthermore, we demonstrate that our method can be used in real-time to simultaneously track the robot's tip position and predict its shape.",

author = "Emile Mackute and Balint Thamo and Kevin Dhaliwal and Mohsen Khadem",

note = "This work was supported by the Medical Research Council MR/T023252/1.; IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022) : IROS Kyoto 2022 ; Conference date: 23-10-2022 Through 27-10-2022",

year = "2022",

month = dec,

day = "26",

doi = "10.1109/IROS47612.2022.9982174",

language = "English",

isbn = "978-1-6654-7928-8",

publisher = "Institute of Electrical and Electronics Engineers",

pages = "3972--3978",

booktitle = "2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",

address = "United States",

url = "https://iros2022.org/",

}

Mackute, E, Thamo, B, Dhaliwal, K & Khadem, M 2022, Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement. in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Institute of Electrical and Electronics Engineers, pp. 3972-3978, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan, 23/10/22. https://doi.org/10.1109/IROS47612.2022.9982174

Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement. / Mackute, Emile; Thamo, Balint; Dhaliwal, Kevin et al.
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Institute of Electrical and Electronics Engineers, 2022. p. 3972-3978.

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

TY - GEN

T1 - Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement

AU - Mackute, Emile

AU - Thamo, Balint

AU - Dhaliwal, Kevin

AU - Khadem, Mohsen

N1 - This work was supported by the Medical Research Council MR/T023252/1.

PY - 2022/12/26

Y1 - 2022/12/26

N2 - Accurate shape estimation of concentric tube robots (CTRs) using mathematical models remains a challenge, reinforcing the need to develop techniques for accurate and real-time shape sensing of CTRs. In this paper, we develop a fusion algorithm that predicts the robot's shape by combining a mathematical model of the CTR with a measurement of the Cartesian coordinates of the robot's tip using an electro-magnetic sensor. We experimentally validated our method in static and dynamic scenarios with and without external loading. Results demonstrated that the fusion algorithm improves the error of model-based shape prediction by an average of 44.3%, corresponding to 2.43% of the robot's arc length. Furthermore, we demonstrate that our method can be used in real-time to simultaneously track the robot's tip position and predict its shape.

AB - Accurate shape estimation of concentric tube robots (CTRs) using mathematical models remains a challenge, reinforcing the need to develop techniques for accurate and real-time shape sensing of CTRs. In this paper, we develop a fusion algorithm that predicts the robot's shape by combining a mathematical model of the CTR with a measurement of the Cartesian coordinates of the robot's tip using an electro-magnetic sensor. We experimentally validated our method in static and dynamic scenarios with and without external loading. Results demonstrated that the fusion algorithm improves the error of model-based shape prediction by an average of 44.3%, corresponding to 2.43% of the robot's arc length. Furthermore, we demonstrate that our method can be used in real-time to simultaneously track the robot's tip position and predict its shape.

U2 - 10.1109/IROS47612.2022.9982174

DO - 10.1109/IROS47612.2022.9982174

M3 - Conference contribution

SN - 978-1-6654-7928-8

SP - 3972

EP - 3978

BT - 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

PB - Institute of Electrical and Electronics Engineers

T2 - IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)

Y2 - 23 October 2022 through 27 October 2022

ER -

Shape Estimation of Concentric Tube Robots Using Single Point Position Measurement

Abstract / Description of output

Publication series

Conference

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Projects

A Cyber-Physical System for Unified Diagnosis and Treatment of Lung Diseases

Cite this