Paper Title
Vision Based Mobile Robotic Simultaneous Localization And Mapping

To navigate in an unknown environment, a mobile robot needs to build a map of the environment and localize itself in the map at the same time. The process addressing this dual problem is called Simultaneous Localization And Mapping (SLAM). This paper presents a motion model for planar mobile robot equipped with vision sensor and encoders by applying SLAM method. Because of the nonlinearity of the motion model, Extended Kalman filter (EKF) is used, which has powerful per-formance under nonlinear and multi-modal conditions. A mobile robot with Kinect sensor mounted on it is used to perform Simultaneous Localization and Mapping, SLAM. The main goal is to build a 3D map from RGB and depth information provided by a camera, while the robot navigates avoiding obstacles.