Autonomous Mobile Robot Study in the Context of Maintenance 4.0

Abstract

The popularization of technical objects’ autonomy in various transport branches is reflected in research on autonomous cars, drones, airplanes, ships, trains or mobile robots. Studies on autonomous mobile robots (AMR) mainly focus on navigation, localization, path planning and obstacle detection problems. These are the challenges of performing the defined tasks, i.e., reliable operation. In addition to these challenges, maintenance is an important issue rarely considered in the literature. One can find multiple papers concerning battery management, but there is definitely a lack of papers dedicated to failure consideration in the form of predictive maintenance applications. AMRs are highly complex objects with a serial reliability structure. Corrective and preventive maintenance strategies, used for many years in various objects and systems, are insufficient for such objects. New possibilities for maintenance are provided by the dynamic development of the Industry 4.0 concept. Along with it, the term Maintenance 4.0 has emerged. It assumes mainly the prediction of failures using sensors and machine learning algorithms. Considering AMR in the context of Maintenance 4.0 represents a new challenge not addressed in the literature to this time. The objective of this paper is twofold. Firstly, we would like to present a brief summary of the predictive maintenance methods available in the literature. Secondly, we would like to consider the AMR study for Maintenance 4.0 purposes. A general scheme of predictive maintenance method for AMR is introduced. Initial steps were taken on the example of chosen AMR.