EVOLVING ROBUST ROBOT CONTROLLERS FOR CORRIDOR FOLLOWING USING GENETIC PROGRAMMING

被引：0

作者：

Wyns, Bart ^{[1
]}

Bonte, Bert ^{[1
]}

Boullart, Luc ^{[1
]}

机构：

[1] Univ Ghent, Dept Elect Energy Syst & Automat, Technol Pk 913, Zwijnaarde, Belgium

来源：

ICAART 2010: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1: ARTIFICIAL INTELLIGENCE | 2010年

关键词：

Genetic programming; Evolutionary robotics; Corridor following; EyeBot;

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：

Designing robots and robot controllers is a highly complex and often expensive task. However, genetic programming provides an automated design strategy to evolve complex controllers based on evolution in nature. We show that, even with limited computational resources, genetic programming is able to evolve efficient robot controllers for corridor following in a simulation environment. Therefore, a mixed and gradual form of layered learning is used, resulting in very robust and efficient controllers. Furthermore, the controller is successfully applied to real environments as well.

引用

页码：443 / 446

页数：4