Dynamic localization of mobile robot based on triangulation centroid estimation

Abstract

According to the inbuilding disaster rescue system failure in network blind spots, a self-dynamic localization system of mobile robot, which can dynamically choose beacon node and determine centroid of intersection based on circles of three beacon nodes, was proposed. This method can apply Received Signal Strength Indication (RSSI) for distance measurement. Geometric Contraints-based Triangle Centroid Estimation (GCTCE) fulfilled the localization. Kalman filter was integrated with the proposed localization to realize the error-correct. The errors caused by the interference of the environmental noises can be minimized efficiently. Especially in network blind spots, the Kalman filter provides optimal data. Simulation and experimental results showed the accuracy and adaptivity of the self-dynamic localization of mobile robots.