Novelty-based visual inspection using mobile robots

Abstract

In this paper we present a novelty detection mechanism in which a mobile robot learns a model for its environment through visual exploration. Once the learning process is finished, the robot can be used to inspect the environment and highlight stimuli that do not fit the acquired model of normality. Experimental results from a visual inspection task involving the detection of arbitrary objects are also presented in this paper.