The lagr project - integrating learning into the 4D/RCS control hierarchy

ICINCO-RA Pub Date : 2006-08-01 DOI:10.5220/0001210701540161
J. Albus, R. Bostelman, T. Hong, Tommy Chang, W. Shackleford, M. Shneier
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引用次数: 10

Abstract

The National Institute of Standards and Technology's (NIST) Intelligent Systems Division (ISD) is a par- ticipant in the Defense Advanced Research Project Agency (DARPA) LAGR (Learning Applied to Ground Robots) Project. The NIST team's objective for the LAGR Project is to insert learning algorithms into the modules that make up the 4D/RCS (Four Dimensional/Real-Time Control System), the standard reference model architecture to which ISD has applied to many intelligent systems. This paper describes the 4D/RCS structure, its application to the LAGR project, and the learning and mobility control methods used by the NIST team's vehicle.
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更大的项目-将学习整合到4D/RCS控制层次结构中
美国国家标准与技术研究院(NIST)智能系统部(ISD)是美国国防高级研究计划局(DARPA) LAGR(学习应用于地面机器人)项目的参与者。NIST团队对LAGR项目的目标是将学习算法插入到组成4D/RCS(四维/实时控制系统)的模块中,这是ISD应用于许多智能系统的标准参考模型架构。本文介绍了4D/RCS结构及其在LAGR项目中的应用,以及NIST团队车辆使用的学习和移动控制方法。
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