Temporal and spatial 3D motion vector filtering based visual odometry for outdoor service robot

This paper describes a visual odometry algorithm that deals with the nearly degenerated situation caused by a false motion vector generated by independently moving objects, repetitive patterns and wrong depth information that often arise in visual odometry for outdoor service robots. To filter out these false motion vectors, we use temporal and spatial motion vector filter. The temporal motion vector filter uses the previous motion models to filter out abruptly changed motion vectors, and the spatial motion vector filter uses the motion vector´s length information and the motion vector´s direction information. The direction information of the motion vectors generated by independently moving objects are different from the direction of the vector generated by camera movement in 3D space, and the length information of the motion vector caused by triangulation error is different from the correctly triangulated points. We uses voting scheme to determine primary motion vectors. This algorithm has been tested on a service robot that works in outdoor environment. By using our method, we can deal with independently moving objects and problem caused by repetitive patterns and triangulation errors.