High-Precision Self-Positioning of Inspection Robot When it is Located at the Edge of the Cell

The high-accuracy self-positioning of the inspection robot is the key to ensure the accuracy of the inspection task. The existing location solutions do not solve the problem of low positioning accuracy when the robot is located at the edge of the cell. The positioning method based on received signal strength (RSS) is a low-cost positioning scheme. However, this method is greatly affected by the fluctuation of the RSS, which leads to the poor positioning accuracy of the target, especially for the target located at the edge of the cell. Meanwhile, the positioning accuracy is also related to the location distribution of the access point (AP). A three-step optimization algorithm based on RSS and AP layout is proposed in this paper to improve the localization accuracy of the inspection robots when it is at the edge of the cell. First, the optimal AP layout with the highest positioning accuracy is selected based on the maximization of Fisher information matrix. Then the matrix is decomposed based on the active set method. Finally, for different initial user estimation position, the positioning accuracy of the user is further improved using an improved extended min-max method. Simulation results show that the optimal AP layout ensures the lowest positioning error compared with the specified and the worst layout scenario. In the case of six optimal AP layouts, the positioning accuracy of the proposed algorithm is improved by 16.07%, 48.35% and 17.54% compared with the min max strategy, the min-max algorithm with area partition strategy and the traditional Taylor series expansion method respectively.