Real-time object pose recognition and tracking with an imprecisely calibrated moving RGB-D camera

Abstract

We introduce a real-time system for recognizing and tracking the position and orientation of a large number of complex real-world objects, together with an articulated robotic manipulator operating upon them. The proposed system is fast, accurate and reliable and yet does not require precise camera calibration. The key to this high level of performance is a continuously-refined internal 3D representation of all the relevant scene elements. Occlusions are handled implicitly in this approach and a soft-constraint mechanism is used to obtain the highest precision at a specific region-of-interest. The system is well-suited for implementation on Graphics Processing Units and thanks to a tight integration of the latter's graphical and computational capability, scene updates can be obtained at framerates exceeding 40 Hz. We demonstrate the robustness and accuracy of this system on a complex real-world manipulation task involving active endpoint closed-loop visual servo control in the presence of both camera and target object motion.