Efficient camera-based pose estimation for real-time applications

Authors:
Elmar Mair;Klaus H. Strobl;Michael Suppa;Darius Burschka
Affiliations:
Department of Informatics, Technische Universität München, Garching, Germany;Institute for Robotics and Mechatronics, German Aerospace Center, Münchner, Wessling, Germany;Institute for Robotics and Mechatronics, German Aerospace Center, Münchner, Wessling, Germany;Department of Informatics, Technische Universität München, Garching, Germany
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

Accurate online localization is crucial for mobile robotics. In this paper, we describe a real-time image-based localization technique, which is based on a single calibrated camera. This can be supported by a second camera to improve accuracy and to provide the correct translational scale. Our goal is a robust and unbiased pose estimation in highly dynamic scenes on resource-limited systems. The presented approach is characterized through significantly improved robustness of the pose estimation, a novel approach for stereo subpixel accurate landmark initialization, and the speed-up of conventional tracking routines to achieve online capability. Although the algorithm is designed for accurate, online short-range egomotion estimation in hand-held scanning devices, it can be used for any mobile robot application as shown in this paper. Various tests and experimental results with a mobile platform and a hand-held 3D modeler are presented and discussed.