MSMS: Multiplexing Sensors and Maps System for Robust Localization by Leveraging Effective Sensors and Maps

Because autonomous mobile robots require pose information for navigation, localization is crucial. Localization estimates a robot’s pose by matching currently observed features with a pre-constructed map. However, each sensor has environments in which the localization accuracy deteriorates owing to the environmental dependency of the sensors, making robust localization with a single sensor difficult. Sensor multiplexing methods have been proposed to address this issue. In addition, condition changes can alter observed environmental features, causing mismatches between current observations and the map because of the condition dependency of maps. This makes robust localization in such environments difficult. Map multiplexing methods have been proposed to address this. Robust localization can be achieved against the environmental dependency of sensors by multiplexing sensors and against the condition dependency of maps by multiplexing maps. However, multiplexing using sensors or maps is insufficient to achieve robust localization against both types of dependency. Hence, in this paper, we propose a system that multiplexes both sensors and maps. Experiments using a dataset confirmed that the proposed system achieved robust localization against both types of dependency.