The use of Visual Odometry（VO） for planetary rover localization has been extensively researched.Traditionally

motion estimation is resolved only between adjacent frames;this neglected stronger geometric constraints possible from processing multiple consecutive frames.This paper presents a new visual odometry method based on bundle adjustment of an image network formed by feature tracking among multiple consecutive frames.In the feature-tracking process

outliers are detected based on the consistency of Euclidean distances in different stereo frames;geometric key frames are selected adaptively.Additionally

analysis of VO accuracy with respect to the geometric configuration of stereo camera is performed using Monte Carlo simulation.Results of field experiments demonstrate the effectiveness of the proposed method in improving localization accuracy.