Because the visual information is easily affected by external environment factors
therefore the selected feature points of mobile robot based on visual simultaneous localization and map building requires high stability and good robustness. For the problem of monocular visual mobile robot SLAM(Simultaneous Localization and Mapping)
a kind of mono-SLAM algorithm based on Extended kalman filter is proposed by using SURF(Speed Up Robust Features) feature points and the inverse depth method. The process of SLAM is completed by fusing the information of SURF features and robot information with EKF. The result of simulation experiment indicates that the proposed algorithm is feasible
and with high localization precision in indoor structured environment.
Montiel A J,Civera J.Unified Inverse Depth Parametrization for Monocular Slam[C].Philadelphia,Penrsylvania:In Robotics Science and Systems Conference,2006:16-19.