Research Of Simultaneous Localization And Map Building Problem Using On AUV

The work of this thesis stems from preliminary research project- "The Distributed Controls of Multi-autonomous Underwater Vehicle" , This thesis deals with the Simultaneous Localization and Mapping algorithm when mobile systems in unknown environments. Simultaneous Localization and Mapping (SLAM) as defined in this thesis is the process of concurrently building up a map of the environment and using this map to obtain improved estimates of the location of the vehicle.In this thesis, The chapter begins with a brief overview of the AUV and the SLAM. This is followed by a section discussing the structure of the SLAM problem, analysis of a conventional and well known SLAM algorithm -Absolute Map Filter or AMF. Then this thesis presents another SLAM algorithm-the Relative Map Filter, The RMF is however disadvantaged by the inability to guarantee consistency of the estimated relative map. The following sections introduce a new navigation filter - the Geometric Projection Filter or GPF. The consistency of the estimated relative map is enforced by the application of the constrained estimator to an inconsistent relative map produced by a standard RMF. This thesis presents a simulation of the AMF to illustrate these SLAM algorithms.