Fusing laser and image data for 3D perceived space representations

In this paper a fusion technique is presented for 3-D representation of space. The technique is based on a fusion process which involves laser range data and segmented image data with human expertise related with the surrounding environment. In particular, the range data may contain noise due to reflections on sloped surfaces or long distance open corridors, thus the proposed fusion approach removes the noise by using human expertise from 3-D environments. This method could be utilized either by an autonomous robot in an unknown environment, or by an inspection machine in a complex manufacturing environment, or by a visual navigation device used by blind people. Additional applications for this technique are the ability to correct measurement deficiencies in a laser-scan and to provide a true color and 3-D perceived shape representation for a given object in a modeling environment.