Author:
Aoyagi Seiji, ,Hattori Nobuhiko,Kohama Atsushi,Komai Sho,Suzuki Masato,Takano Masaharu,Fukui Eiji,
Abstract
For simultaneously localizing and mapping (SLAM) an indoor mobile robot, a method to process a monocular image of entire environmental view is proposed. To ensure that an object can be searched for, invisible floor marks are proposed for modifying the environment and which are useful in narrowing the search area in an image. Specifically our approach involves: 1) narrowing the searched area using invisible floor marks, 2) extracting features based on scale-invariant feature transform (SIFT), 3) using template matching with SIFT features assisted by partial templates and the spatial relationship to the floor, and 4) verifying object recognition with an AdaBoost classifier using Haar-like features based on object shape information. A robot is localized relative to the floor using the floor marks, then, objects in a clattered image are extracted and recognized, and 3D solid models of them are mapped on the floor to build a highly structured 3D map. Recognition was over 80% successful, including tables and chairs and taking several tens of seconds per 640 × 480 pixel image.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference23 articles.
1. S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” Cambridge, MA New York, MIT Press, 2005. (Japanese version by R. Ueda, Mainichi-Communications, 2007).
2. A. Davison, “Real-time Simultaneous Localization and Mapping with a Single Camera,” in Proc. ICCV, pp. 1403-1410, Nice, France, 2003.
3. M. Tomono, “3-D Object Map Building Using Dense Object Models with SIFT-based Recognition Features,” in Proc. IROS 2006, pp. 1885-1890, Beijing, China, 2006.
4. R. Sim and J. J. Little, “Autonomous Vision-Based Exploration and Mapping Using Hybrid Maps and Rao-Blackwellised Particle Filters,” in Proc. IROS 2006, pp. 2082-2089, Beijing, China, 2006.
5. R. Kurazume, H. Yamada, K. Murakami, Y. Iwashita, and T. Hasegawa, “Target Tracking Using SIR and MCMC Particle Filters by Multiple Cameras and Laser Range Finders,” in Proc. IROS 2008, pp. 3838-3844, Nice, France, 2008.
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