Towards real-Time shape sensing of continuum manipulators utilizing fiber Bragg grating sensors

Amirhossein Farvardin, Ryan J. Murphy, Robert B. Grupp, Iulian Iordachita, Mehran Armand

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

Abstract

Fiber Bragg grating (FBG) sensors are a promising tool for real-Time shape reconstruction of dexterous continuum manipulators (DCM). We have recently developed a novel FBG-based shape sensor which is capable of detecting a radius of curvature of 15 mm for a 35 mm length DCM. This paper aims to further evaluate the accuracy of this shape sensor during motion of the DCM. Different experiments were performed including free bending, bending in the presence of an obstacle, and bending with a tool inserted in the lumen of the DCM. Results indicate that this sensor can track the tip position with an average error of 0.81 mm for free bending, 2.73 mm for bending with an obstacle, and 0.93 mm for bending with a tool.

Original languageEnglish (US)
Title of host publication2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics, BioRob 2016
PublisherIEEE Computer Society
Pages1180-1185
Number of pages6
ISBN (Electronic)9781509032877
DOIs
StatePublished - Jul 26 2016
Event6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2016 - Singapore, Singapore
Duration: Jun 26 2016Jun 29 2016

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2016-July
ISSN (Print)2155-1774

Other

Other6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2016
CountrySingapore
CitySingapore
Period6/26/166/29/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Towards real-Time shape sensing of continuum manipulators utilizing fiber Bragg grating sensors'. Together they form a unique fingerprint.

Cite this