Global Round-up Strategy Based on an Improved Hungarian Algorithm for Multi-robot Systems

In this paper, a round-up strategy is proposed to optimize global target selection and improve the efficiency of multi-robot round-up behavior, which is applicable to the round-up situation with multiple pursuers and multiple evaders. Firstly, a constrained pursuer control strategy is designed to maintain the effectiveness of the area-minimizing round-up strategy. Additionally, a novel and detailed procedure is presented to make the area-minimizing round-up strategy based on Voronoi easier to understand. Then, an improved Hungarian algorithm-based global optimization strategy for target selection is proposed. This algorithm aims to reduce the efficiency due to the uneven position distribution of the robots. Finally, experimental results are given to demonstrate the proposed strategy can improve the global efficiency of multi-robot round-up.