Markerless Augmented Reality for Robots in Unprepared Environments

Abstract

Augmented Reality (AR) can assist humans in understanding complex robot information, and improve Human and Robot Interaction (HRI). However, many restrictions are imposed by the underlying technology used and thus have lim- ited current AR systems to operate in con- trolled or modi ed robot environments. This hinders the wide spread use of AR for di er- ent robot applications. This paper presents a markerless AR system that combines recent tracking and detection techniques for AR vi- sualisation of robot task relevant information. We employ natural feature tracking techniques to compute the camera pose for accurate reg- istration of virtual objects. Automatic relocal- isation of the camera pose is achieved using a planar object detection algorithm which recov- ers from tracking failures. Experiments using a camera mounted on a mobile ground robot demonstrated accurate tracking and successful recovery of planar features in an unprepared indoor environment.