Active leading through obstacles using ant-colony algorithm

作者：Vatankhah Ramin; Etemadi Shahram^*; Alasty Aria; Vossoughi Gholam Reza; Boroushaki Mehrdad

来源：Neurocomputing, 2012, 88: 67-77.

DOI：10.1016/j.neucom.2011.08.030

• Multi-agents
• Active leader
• Fast flocking
• Ant colony algorithm

In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective.

• 出版日期2012-7-1