进化复合机器人行为——模块化架构

Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05. Pub Date : 2005-06-23 DOI:10.1109/ROMOCO.2005.201435

Tobias Larsen, S. Hansen

{"title":"进化复合机器人行为——模块化架构","authors":"Tobias Larsen, S. Hansen","doi":"10.1109/ROMOCO.2005.201435","DOIUrl":null,"url":null,"abstract":"We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.","PeriodicalId":142727,"journal":{"name":"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Evolving composite robot behaviour - a modular architecture\",\"authors\":\"Tobias Larsen, S. Hansen\",\"doi\":\"10.1109/ROMOCO.2005.201435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.\",\"PeriodicalId\":142727,\"journal\":{\"name\":\"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMOCO.2005.201435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMOCO.2005.201435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 20

摘要

我们开发了一种复合控制系统，用于解决自主机器人的复杂任务。控制系统采用人工进化的方法进行进化，可以看作是一个模块化的决策树，每个节点都是一个神经网络。结果表明，该控制系统对噪声具有鲁棒性、无功性、可扩展性和可自动设置组态。此外，我们还展示了现实世界中的机器人使用该控制系统工作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Evolving composite robot behaviour - a modular architecture

We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.

自引率

0.00%

发文量