V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery
- https://doi.org/10.2991/ifsa-eusflat-15.2015.208How to use a DOI?
- Soft computing, robotic-assisted surgery, force estimation.
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.
- © 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 - https://doi.org/10.2991/ifsa-eusflat-15.2015.208 ID - Aviles2015/06 ER -