Agent-oriented robot task transformation

W. Kalkhoff
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引用次数: 1

Abstract

This paper describes a new approach to modelling robot systems by a large number of cooperating agents solving a robot task. On the one hand the agent model submits to use results of the distributed artificial intelligence (DAI), on the other hand, typical aspects of robot systems must be integrated. Therefore, an agent model will be presented serving the special requirements of robot systems and offering many advantages like robustness, high efficiency, and the chance of integrating reactive and deliberative behavior. The agent model also enables the use of different programming paradigms, ranging from complex over hierarchical to object-oriented agents. Finally, a typical set of agents is presented, forming a multi-layered, distributed and reactive (MDR) robot task-level transformer.
面向智能体的机器人任务转换
本文描述了一种通过大量协作智能体解决机器人任务来建模机器人系统的新方法。智能体模型一方面向分布式人工智能(DAI)的应用成果提交,另一方面必须集成机器人系统的典型方面。因此,将提出一种智能体模型,以满足机器人系统的特殊要求,并具有鲁棒性、高效率以及将反应性和协商性行为整合在一起的机会等优点。代理模型还支持使用不同的编程范例,从复杂的分层代理到面向对象的代理。最后,给出了一组典型的智能体,构成了一个多层、分布式和无功(MDR)机器人任务级变压器。
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