V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery
Tipo de documentoTexto en actas de congreso
Fecha de publicación2015
Condiciones de accesoAcceso abierto
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.
CitaciónAviles, 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.