PT Unknown
AU David Aldavert
   Ricardo Toledo
   Arnau Ramisa
   Ramon Lopez de Mantaras
TI Visual Registration Method For A Low Cost Robot: Computer Vision Systems
BT 7th International Conference on Computer Vision Systems
PY 2009
BP 204–214
VL 5815
DI 10.1007/978-3-642-04667-4_21
AB An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance.
ER