Efficient localization using particle filter with clustering considering obstacles

In this paper, a new efficient localization method based on particle filter with clustering is proposed. Particle filter is one of the most powerful methods for localization of autonomous robots. Accuracy and efficiency of the localization depend on decision making of movement of robot. Yamashita proposed a decision making method for effective localization by using clustering of particles. Clustering of particle can significantly reduce the amount of calculation. We modify distance between particles in clustering in consideration of obstacles for improving the localization ability. Simulation results show the effectiveness of the proposed method.