A simultaneous planning localization and mapping approach for robust navigation

This paper presents an algorithm for solving the simultaneous planning localization and mapping (PSLAM) problem, an important key issue for robust navigation in unknown environments. This proposal is a method for integrated exploration, where mobile robot incrementally build a map of this environment while simultaneously use this map to compute the absolute robot localization, and make local decisions on where to move next in order to minimize the error in the estimation of the mobile pose and the configuration locations. The continuous localization process is based on the extended Kalman filter (EK). We present simulated and experimental results on the Pionner 3DX robot to show the performance of the proposed strategy.