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We require knowing the real time location of a small sized ground robotic vehicle when it performs any task indoors or outdoors. I am implementing low cost, self contained localization system for small sized vehicles. SLAM provides most accurate real time, 3D positions in both indoor as well as outdoor environments. Unlike other localization schemes it does not require external reference, expensive hardware, and strict calibration which are capable of operating in different environments. It identifies relative movement through compass sensor and MEMS sensor. It also corrects the localization drift by GPS augmentation. The complexity of the technical processes of locating and mapping under conditions of errors and noise do not allow for a coherent solution of both tasks. Simultaneous localization and mapping (SLAM) is a concept that binds these processes in a loop and therefore supports the continuity of both aspects in separated processes.

SLAM: Simultaneous Localization and Mapping of small sized ground robotic vehicles