Ant colony optimisation algorithm-based multi-robot exploration. (1st January 2013)

• Record Type: Journal Article
• Authors: Xiao, Benjie; Su, Hongming; Zhao, Yilu; Chen, Xiong
• Is Part Of: International journal of modelling, identification and control. Volume 18:Number 1(2013)
• Page Start: 41
• Page End: 46
• Publication Date: 2013-01-01
• Subjects: multi-robot -- coordinated exploration -- ant colony optimisation -- ACO; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

The key problem of multi-robot exploration in unknown environment is how to appropriately select targets for the robots. In this paper, we present a new method to guide multi-robot exploration. Ant colony optimisation (ACO) is introduced to find the optimal target assignment for the robots. A new cost function is designed which takes into account distance, target position and robot density. The simulation results demonstrated that the proposed method effectively solves the problem of optimal target assignment and exploration efficiency is much increased.