首页 /研究 /Evolving neuro-modules and their interfaces to control autonomous robots
LEARNING

Evolving neuro-modules and their interfaces to control autonomous robots

Bruno Lara, Martin Hülse, Frank Pasemann

发表年份
2001
引用次数
5

摘要

An evolutionary algorithm for the creation of recurrent network structures is presented. The aim is to develop neural networks con-trolling the behaviour of miniature robots. Two neuro-modules are created separately using this evolutionary approach. The first neuro-module gives the agents the ability to move within an environment without colliding with obstacles. The second neuro-module provides the agents with a phototropic behaviour. The interaction of the neuro-modules is then investigated evolving the necessary interface to pro-vide the agents with a coherent obstacle avoidance and phototropic behaviour. The evolution process is carried out in a simulated envi-ronment and individuals with high performance are also tested on a physical environment with the use of Khepera robots.

关键词

RobotComputer scienceObstacle avoidancePhototropismObstacleInterface (matter)Process (computing)Artificial neural networkArtificial intelligenceDistributed computing

相关论文

查看 LEARNING 分类全部论文