Evolving Collision Avoidance on autonomous robots

被引：0

作者：

Koenig, Lukas ^{[1
]}

Schmeck, Hartmut ^{[1
]}

机构：

[1] Univ Karlsruhe, AIFB, Karlsruhe, Germany

来源：

BIOLOGICALLY-INSPIRED COLLABORATIVE COMPUTING | 2008年 / 268卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Utilizing the collective behavior of a population of interacting individuals, based on rather simple local algorithms, is a promising approach for achieving complex goals. We use an onboard online evolutionary model, based on finite Moore automata, to develop collective behavior in an artificial swarm of micro-robots. Experiments have been made in simulation to achieve Collision Avoidance. The model is shown to be capable to generate the desired behavior and we present experiments for adjusting the parameters of the evolutionary optimization.

引用

页码：85 / 94

页数：10

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