实时环境下机器人系统的多智能体体系结构

Chris Micacchi, R. Cohen
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引用次数: 5

摘要

在本文中,我们探讨了为多智能体系统设计架构和处理算法的主题,其中智能体需要在软实时约束下操作时处理环境中的意外事件。我们研究了以下子主题:(1)确定社区中代理的适当自治级别,(2)管理支持新任务分配所需的通信(包括解决可能的障碍),以及(3)对软实时约束的敏感。更具体地说,我们允许某些代理自主操作,并提供协调代理,以避免代理之间协商的一些开销。通过示例,我们说明了该框架对各种机器人应用程序的有用性。特别地,我们讨论了模拟机器人环境(如RoboCup搜索和救援)框架的潜力,这些环境非常适合支持完全自主的代理和由主管控制的代理的组合。我们简要地讨论了一个实现,以证明我们模型的有效性,并强调在机器人应用的实时限制下操作时减少通信和加快处理的必要性。
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A Multi-Agent Architecture for robotic Systems in Real-Time Environments
In this paper we explore the topic of designing an architecture and processing algorithms for a multi-agent system where agents need to address unexpected events in the environment while operating under soft real-time constraints. We examine the subtopics of (1) determining the appropriate level of autonomy for the agents in the community, (2) managing the communication required to support the allocation of new tasks (including ones to address possible obstacles), and (3) being sensitive to soft real-time constraints. More specifically, we allow for certain agents to operate autonomously and also provide for a coordinator agent, to avoid some overhead in negotiation among agents. Using examples, we illustrate the usefulness of the framework for various robotics applications. In particular, we discuss the potential of the framework for simulated robotics environments such as the RoboCup Search and Rescue, which are well suited to supporting a combination of agents that are fully autonomous and agents that are controlled by a supervisor. We briefly discuss an implementation to demonstrate the effectiveness of our model and emphasize the need to reduce communication and expedite processing when operating under real-time constraints for robotics applications.
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