V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery
Document typeConference report
Rights accessOpen Access
Accurate and robust estimation of applied forces in 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.
CitationAviles, A., Alsaleh, S., Montseny, E., Casals, A. V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery. A: World Congress of the International-Fuzzy-Systems-Association. "Proceedings of the 16th World Congress of the International-Fuzzy-Systems-Association (IFSA) / 9th Conference of the European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT). Advances in Intelligent Systems Research". Gijón: Atlantis Press, 2015, p. 1465-1472.