M-ANCHORO: Mobile Anchor Node-Based Path Optimization for Full Coverage Path Planning Algorithm

Abstract

Localization is a key technology in wireless sensor network (WSN) applications. The use of mobile anchor nodes (MANs) to assist in sensor localization is a feasible solution for reducing deployment costs and overcoming geographical limitations. However, real-world environments often contain obstacles with signal-blocking characteristics. Random collision methods cannot guarantee that sensors receive sufficient localization information, resulting in the generation of many redundant beacon points by MANs. To achieve complete localization coverage and improve localization accuracy, we propose a path planning and optimization algorithm called M-ANCHORO. The proposed algorithm divides subregions based on obstacle distribution information and deploys beacon points in equilateral triangles. It then uses the SCAN method to plan a fully localized coverage path and optimizes the number of beacon points using a path simplification procedure to establish a trajectory for full localization coverage. Experimental results showed that M-ANCHORO outperformed Z-curve, SLMAT, and SCAN in terms of localization accuracy and coverage.