空间探索自治协会

B. Simpson, C. Rouff, Joe Roberts, Gary Edwards
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引用次数: 0

摘要

NASA更加重视机器人探索。与人类控制器相比,机器人的复杂程度在不断提高,而它们的成本却在下降。正因为如此,不仅机器人和航天器被赋予了更多的自主权,而且多个机器人和航天器协同工作进行探索的概念正在开发中。然而,仅仅是自主性,缺乏自主性,将使航天器和其他系统容易受到恶劣环境的影响,而且很可能会导致性能下降,系统被破坏或无法从故障中恢复。我们正在致力于协作自主智能伙伴的开发,以支持载人和无人系统在探索和其他应用方面的需求。关联系统在具有大量数据、复杂动作阵列、关键响应时间和可用专家数量有限的领域非常有用,所有这些都适用于空间探索任务。本文描述了一个高级协作关联体系结构,并概述了用于建模的概念图、用于规划的计划目标图以及用于执行协作关联的上下文定位脚本的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomic Associate for Space Exploration
Greater emphasis at NASA is being given to robotic exploration. The sophistication of robots is increasing while their cost is decreasing in comparison to human controllers. Because of this, not only are robots and spacecraft being given more autonomy, but concepts for multiple robots and spacecraft to work together to perform exploration are being developed. Autonomy alone though, absent autonomicity, will leave spacecraft and other systems vulnerable to the harsh environment in which they work and most likely performance will degrade, the system destroyed or it will not be able to recover from faults. We are working on the development of collaborative autonomic intelligent associates to support the needs of manned and unmanned systems for exploration and other applications. Associate systems are useful in domains with large volumes of data, complex array of actions, critical response times, and limited number of experts available, all of which apply to space exploration missions. This paper describes a high level collaborative associate architecture and gives an overview of the use of concept graphs for modeling, plan goal graphs for planning, and context situated scripts for execution of collaborative associates.
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