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To determine the 3D orientation and 3D location of objects in thesurroundings of a camera mounted on a robot or mobile device, we developed twopowerful algorithms in object detection and temporal tracking that are combinedseamlessly for robotic perception and interaction as well as Augmented Reality(AR). A separate evaluation of, respectively, the object detection and thetemporal tracker demonstrates the important stride in research as well as theimpact on industrial robotic applications and AR. When evaluated on a standarddataset, the detector produced the highest f1-score with a large margin whilethe tracker generated the best accuracy at a very low latency of approximately2 ms per frame with one CPU core: both algorithms outperforming the state ofthe art. When combined, we achieve a powerful framework that is robust tohandle multiple instances of the same object under occlusion and clutter whileattaining real-time performance. Aiming at stepping beyond the simple scenariosused by current systems, often constrained by having a single object in absenceof clutter, averting to touch the object to prevent close-range partialocclusion, selecting brightly colored objects to easily segment themindividually or assuming that the object has simple geometric structure, wedemonstrate the capacity to handle challenging cases under clutter, partialocclusion and varying lighting conditions with objects of different shapes andsizes.

6D Object Pose Estimation with Depth Images: A Seamless Approach for Robotic Interaction and Augmented Reality