Global Round-up Strategy Based on an Improved Hungarian Algorithm for Multi-robot Systems
Meng Zhou, Jianyu Li, Chang Wang, Jing Wang, Vicenç Puig
- 发表年份
- 2024
- 引用次数
- 3
- 访问权限
- 开放获取
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002