A bio-inspired cooperative algorithm for distributed source localization with mobile nodes.

In this paper we propose an algorithm for distributed optimization in mobile nodes. Compared with many published works, an important consideration here is that the nodes do not know the cost function beforehand. Instead of decision-making based on linear combination of the neighbor estimates, the proposed algorithm relies on information-rich nodes that are iteratively identified. To quickly find these nodes, the algorithm adopts a larger step size during the initial iterations. The proposed algorithm can be used in many different applications, such as distributed odor source localization and mobile robots. Comparative simulation results are presented to support the proposed algorithm.