Floor Segmentation by Computing Plane Normals from Image Motion Fields for Visual Navigation

This paper proposes a method of detecting movable paths during visual navigation for a robot operating in an unknown structured environment. The proposed approach detects and segments the floor by computing plane normals from motion fields in image sequences. A floor is a useful object for mobile robots in structured environments, because it presents traversable paths if existing static or dynamic objects are removed effectively. In spite of this advantage, it cannot be easily detected from 2D image. In this paper, some geometric features observed in the scene and assumptions about images are exploited so that a plane normal can be employed as an effective clue to separate the floor from the scene. In order to use the plane normal, two methods are proposed and integrated with a designed iterative refinement process. Then, the floor can be accurately detected even when mismatched point correspondences are obtained. The results of preliminary experiments on real data demonstrate the effectiveness of the proposed methods.