Active navigation vision based on eigenspace analysis

The parametric eigenspace method was proposed by Murase-Nayar (1995) to recognize objects and their poses. It could be applied to robot navigation to locate the robot position. However, since similar images may often be taken at multiple locations in real scenes, it cannot always give the robot position reliably with a single image input. This problem can be solved using active vision, that is, combining localization results for images taken at multiple camera positions. Since similar images are projected to points close to one another in the eigenspace, we can tell before actual navigation when we cannot expect reliable localization results with a single image by examining the eigenspace. Moreover, further analysis of the eigenspace can give the best action sequences of camera motion to efficiently localize the robot position. This paper presents such an eigenspace analysis method. Experimental results show the effectiveness of the method.