Besada Portas, EvaLópez Orozco, José AntonioLanillos Pradas, PabloCruz García, Jesús Manuel de la2023-06-202023-06-202012-031424-822010.3390/s120302487https://hdl.handle.net/20.500.14352/43702This work has been supported by the Spanish Grants DPI2009-14552-C02-01 and CAM S-0505/DPI 0391.This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.engAtribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/journal articlehttp://www.mdpi.com/1424-8220/12/3/2487/pdfhttp://www.mdpi.com/1424-8220/12/3/2487/pdfhttp://www.mdpi.comopen access004Multisensor FusionControl-SystemsTrackingLenguajes de programación1203.23 Lenguajes de Programación