Correcting angle of visual odometry system by fusing monocular and stereo methods in untextured dynamic environment

In this research, we propose state-of-the-art 6-Degrees-Of-Freedom (6DOF) visual odometry (VO) system which fused stereo VO with effective feature sampling, VO using normal vector information of a ground plane and monocular VO. Firstly, stereo VO is used to do 6DOF motion estimation in untextured dynamic environments. Secondly, ground plane information is used to improve the accuracy of roll and pitch angles estimation. Thirdly, monocular VO is introduced to solve the problems in stereo processing. Finally, Unscented Kalman Filter is adopted for the fusion of the information acquired from three kinds of VO techniques to accomplish robust and accurate localization. We present and evaluate experimental results for our system over 730 meters runs in a challenging outdoor environment and compare it with ground truth. Proposed VO system can localize the robot´s position within 3.2% error in untextured outdoor environment.