BEECLUST used for exploration tasks in Autonomous Underwater Vehicles

被引：10
|
作者：
Bodi, Michael [1 ]
Moeslinger, Christoph [1 ]
Thenins, Ronald [1 ]
Schmickl, Thomas [1 ]
机构：
[1] Karl Franzens Univ Graz, Dept Zool, Artificial Life Lab, A-8010 Graz, Austria
来源：
IFAC PAPERSONLINE | 2015年 / 48卷 / 01期
关键词：
Swartrt Intelligence; Artificial Life; Emergent Behaviour; Underwater Robotics; COLLECTIVE DECISION-MAKING; AGGREGATION; BEHAVIOR;
D O I：
10.1016/j.ifacol.2015.05.133
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Underwater exploration is still a difficult task these days. In this paper we suggest a swarm of Autonomous Underwater Vehicles (AUVs) for such tasks. These AUVs are controlled by BEECLUST which is a swarm control algorithm inspired by honeybee behaviour. A swarm controlled by BEECLUST shows very reliable aggregation behaviour in a global optimum. In a simulation experiment we show that BEECLUST is very well adaptable for AUV swarms. Furthermore we show that BEECLUST is not only capable of showing aggregation behaviour but also is a valid tool for underwater exploration tasks. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：819 / 824
页数：6
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