在多机器人系统中嵌入数据流体系结构的研究

Menaxi J. Bagchi, Divya D. Kulkarni, S. B. Nair, P. K. Das
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引用次数: 0

摘要

在现实世界的机器人系统中,即使机器人正在执行先前分配的任务,也可能需要执行新的任务。这些新工作可以异步地、动态地出现。在本文中,我们提出了一种利用数据流计算概念与移动代理技术相结合的机制,以确保新作业可以在线添加,同时对当前正在执行的作业干扰最小。整个系统不需要因为添加和执行新作业而陷入停顿。提议的机制有助于新作业与当前正在执行的作业同时执行。该机制还有助于使由机器人、嵌入式系统、传感器、个人计算机以及移动和静态代理组成的整个系统以分散和分布式的方式执行。实验在模拟和现实世界中进行,使用这些异构实体来描绘所提出的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Embedding a Dataflow Architecture in a Multi-Robot System
In real-world robotic systems, new jobs may need to be executed even when the robots are executing the ones assigned earlier. These new jobs can crop up asynchronously and on-the-fly. In this paper, we propose a mechanism that uses the concept of dataflow computing coupled with mobile agent technology, to ensure that new jobs can be added online with minimal interference to the currently executing jobs. The entire system need not be brought to a standstill because of the addition and execution of the new jobs. The proposed mechanism facilitates simultaneous executions of the new jobs along with the ones currently executing. The mechanism also helps make the overall system constituting robots, embedded systems, sensors, personal computers, and mobile and static agents, execute in a decentralized and distributed manner. Experiments are conducted in both emulated and real worlds, using such heterogeneous entities to portray the proposed mechanism.
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