Static Path Planning for Mobile Beacons to Localize Sensor Networks

In this paper, we study the static path planning problem with wireless sensor network localization as the primary objective. We consider a model in which sensors are assumed to be uniformly deployed to a predefined deployment area. We then deploy a robot to serve as a mobile beacon to enable the localization of the sensor nodes. The robot follows a pre-determined static path while periodically broadcasting its current location coordinates to the nearby sensors. The static path planning problem looks for good paths that result in better localization accuracy and coverage of the sensor network while keeping the path length bounded. We propose two new path types, CIRCLES and S-CURVES, that are specifically designed to reduce the collinearity during localization. We compare our solution with existing ones using the Cramer Rao bound (CRB) as the evaluation tool, which gives an unbiased evaluation regardless of localization algorithm used. The evaluation shows that our solutions cope with collinearity in a more effective manner than previous solutions. Our solutions provide significantly better localization accuracy and coverage in the cases where collinearity is the greatest problem