Robotic colonoscopy: can high fidelity simulation optimize robot design and validation?

Evans, M. orcid.org/0009-0002-2379-8804, Du, J., Cao, L. et al. (1 more author) (2025) Robotic colonoscopy: can high fidelity simulation optimize robot design and validation? In: 2025 IEEE International Conference on Robotics and Automation (ICRA). 2025 IEEE International Conference on Robotics and Automation (ICRA), 19-23 May 2025, Atlanta, GA, USA. Institute of Electrical and Electronics Engineers (IEEE), pp. 2954-2960. ISBN: 9798331541408.

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Item Type: Proceedings Paper
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© 2025 The Authors. Except as otherwise noted, this author-accepted version of a paper published in 2025 IEEE International Conference on Robotics and Automation (ICRA) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Information and Computing Sciences; Human-Centred Computing; Engineering; Bioengineering; Colo-Rectal Cancer; Cancer; Digestive Diseases
Dates:
  • Published (online): 2 September 2025
  • Published: 2 September 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
Funder
Grant number
Engineering and Physical Sciences Research Council
EP/T517835/1
Engineering and Physical Sciences Research Council
2940227
Date Deposited: 02 Oct 2025 08:24
Last Modified: 02 Oct 2025 08:24
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/icra55743.2025.11128805
Open Archives Initiative ID (OAI ID):

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