Abstract
In this paper, we propose stereo vision based visual odometry with effective feature sampling technique for untextured outdoor environment. In order to extract the feature points in untextured domain, we divide an image into some sections and affect suitable processes for each section. This approach can also prevent concentration of feature points, and ignore the feature points on moving objects. And robust motion estimation is enabled by using the framework of three-point algorithm and RANSAC. Moreover, the accumulation eror is reduced by key frame adjustment. We present and evaluate experimental results for our system in outdoor environment. Proposed visual odometry system can localize the robot's position within 4% error in untextured outdoor environment.
