A camera self-health-maintenance system based on sensor artificial intelligence

Abstract

Autonomous vehicles and robots require increasingly more robustness and reliability to meet the demands of modern tasks. These requirements specially apply to cameras onboard such vehicles because they are the predominant sensors to acquire information about the environment and support actions. However, there are versatile undesirable states cameras can encounter. Hence, cameras must maintain proper functionality and take automatic countermeasures if necessary. Currently, there is only little work that examines the practical use of a general condition monitoring approach for cameras and designs countermeasures in the context of an envisaged high-level application. We propose a self-health-maintenance framework for cameras with focus on blur and noise, based on artificial intelligence and the incorporation of additional physical knowledge of the sensor (Sensor AI).