Cooperative underwater acoustic source searching based on adaptive PSO algorithm

Source searching task is important in many real world applications. Searching a source with complex spatial pattern especially in a large workspace is a challenging task. The task becomes harder if a single robotic platform is used. In underwater perspective, such examples include underwater acoustic source searching which is useful during flight black box searching, mines detection and localizing underwater vehicle applications. In this paper, a new adaptive PSO algorithm to cooperatively search underwater acoustic source for dedicated swarm of autonomous surface vehicles is proposed. In the proposed PSO based searching algorithm, velocity parameters (i.e. inertia weight and acceleration coefficients) are adaptively updated considering the trajectory stability of the robot. In addition, to expedite the convergence speed, each parameter is updated for each robot and each dimension independently at each iteration. To validate the proposed strategy, a simulation study is performed. Simulation results show the reliability and performance improvement of the proposed method compared to several existing search algorithm benchmarks.