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.