V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery
Authors
Angelica I. Aviles, Samar M. Alsaleh, Eduard Montseny, Alicia Casals
Corresponding Author
Angelica I. Aviles
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.208How to use a DOI?
- Keywords
- Soft computing, robotic-assisted surgery, force estimation.
- Abstract
Robotic-Assisted Minimally Invasive Surgery is a very challenging task. Many vision-based solutions attempt to estimate the force by measuring the surface deformation after contacting the surgical tool. However, visual uncertainty, due to tool occlusion, is a major concern and can highly affect the results’ precision. In this paper, a novel design of an adaptive neuro-fuzzy inference strategy with a voting step (V-ANFIS) is used to accommodate with this loss of information. Experimental results show a significant accuracy improvement from 50% to 77% with respect to other proposals.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Angelica I. Aviles AU - Samar M. Alsaleh AU - Eduard Montseny AU - Alicia Casals PY - 2015/06 DA - 2015/06 TI - V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1465 EP - 1472 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.208 DO - 10.2991/ifsa-eusflat-15.2015.208 ID - Aviles2015/06 ER -