多机器人系统自动重组的运行时模型

Christopher Zhong, S. DeLoach
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引用次数: 30

摘要

本文提出了一个可重用的框架,用于使用基于组织的方法为异构机器人团队开发自适应多机器人系统。该框架基于自适应计算系统的组织模型(OMACS)和动态系统的目标模型(GMoDS)。GMoDS用于捕获驱动系统的系统级目标。OMACS是一个抽象模型,用于捕获系统配置,并允许团队在不需要显式运行时重组规则的情况下进行组织和重组。虽然OMACS提供了隐式重组功能,但它还支持可以指导或限制最终组织的策略,从而限制意外的或有害的适应。我们通过设计和实现一个用于检测简易爆炸装置的多机器人系统来展示我们的框架。然后我们强调结果系统的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Runtime models for automatic reorganization of multi-robot systems
This paper presents a reusable framework for developing adaptive multi-robotic systems for heterogeneous robot teams using an organization-based approach. The framework is based on the Organizational Model for Adaptive Computational Systems (OMACS) and the Goal Model for Dynamic Systems (GMoDS). GMoDS is used to capture system-level goals that drive the system. OMACS is an abstract model used to capture the system configuration and allows the team to organize and reorganize without the need for explicit runtime reorganization rules. While OMACS provides an implicit reorganization capability, it also supports policies that can either guide or restrict the resulting organizations thus limiting unexpected or harmful adaptation. We demonstrate our framework by presenting the design and implementation of a multi-robot system for detecting improvised explosive devices. We then highlight the adaptability of the resulting system.
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