An Adaptive Neuro-Fuzzy-based Multisensor Data Fusion applied to real-time UAV autonomous navigation - Paulino, Ângelo de C.; Shiguemori, Elcio H.; Guimarães, Lamartine N. F. (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2018)
The world trend in employing UAVs and drones is remarkable. The main reasons are that they may cost fractions of manned aircraft and avoid the exposure of human lives to risks. However, they depend on positioning systems that may be fallible. Therefore, it is necessary to ensure that these systems are as accurate as possible, aiming at safe navigation. In pursuit of this end, conventional Data Fusion techniques can be employed. Nonetheless, its high computational cost may be prohibitive due to the low payload of some UAVs. This paper proposes a Data Fusion application based on Computational Intelligence – Adaptive-Network-Based Fuzzy Inference System (ANFIS) – which is able to improve the accuracy of such position estimation systems.