Path planning and localization for mobile anchor based wireless sensor networks

Abstract

Abstract-In wireless sensor networks, anchor positions play an important role for accurate localization. For mobile anchor (MA) based scenarios, both the efficiency of the path planning algorithm and the accuracy of the localization mechanism are critical for the best performance. In this work, an adaptive path planning algorithm is proposed based on Gauss-Markov mobility model, while the sensors are localized using alternating minimization approach. Path planning, which combines the velocity adjustment, the perpendicular bisector and the virtual repulsive strategies, is improved by developing virtual attractive force strategy. The surveillance area is divided into grids and a virtual attractive force is applied to the MA in sparsely and densely populated areas. For localization, the non-convex optimization problem is converted into a bi-convex form and solved by alternating minimization algorithm leading to a shorter MA path. The simulation results show that introducing the virtual attractive strategy increases the path planning accuracy and cover more surveillance region using less energy. Furthermore, compared to the linear localization method, the localization accuracy increases when the alternating minimization is used.

Coordinated Path Planning for Surface Acoustic Beacons for Supporting Underwater Localization

“…Note that here the beacon is mobile, while the localization targets -the sensing nodesare static at unknown positions. Other approaches addressing the same problem have been presented in [11], [12], [13]. The distinction in the robotics problem is that both the beacon and the localization targets -the AUVs -are mobile, and the positions of the AUVs are not completely unknown.…”