Evolution of a Cognitive Architecture for Social Robots: Integrating Behaviors and Symbolic Knowledge
Evolution of a Cognitive Architecture for Social Robots: Integrating Behaviors and Symbolic Knowledge
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DOI：
10.3390/app10176067
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发表时间：
2020-09-01
影响因子：
2.7
通讯作者：
Matellan, Vicente
中科院分区：
文献类型：
--
作者：
Martin, Francisco;Rodriguez Lera, Francisco J.;Matellan, Vicente
本文介绍了一种用于控制自主社交机器人的机器人体系结构的演变。该体系结构的第一个实例最初是根据基于行为的原则设计的。该体系结构的构建块是设计为有限状态机的行为，并以行为学启发的方式进行组织。然而，在人机交互中管理明确的符号知识的需要需要将规划能力集成到体系结构中，并对环境和机器人的内部状态进行符号表示。本文的一个主要贡献是描述了整合了这两种方法的工作记忆。这种工作内存已经被实现为分布式图形。另一个贡献是使用行为树而不是状态机来实现体系结构中基于行为的部分。这个最新版本的体系结构已经在机器人比赛(RoboCup或欧洲机器人联赛等)中进行了测试，其性能也在本文中进行了讨论。
This paper presents the evolution of a robotic architecture intended for controlling autonomous social robots. The first instance of this architecture was originally designed according to behavior-based principles. The building blocks of this architecture were behaviors designed as a finite state machine and organized in an ethological inspired way. However, the need of managing explicit symbolic knowledge in human-robot interaction required the integration of planning capabilities into the architecture and a symbolic representation of the environment and the internal state of the robot. A major contribution of this paper is the description of the working memory that integrates these two approaches. This working memory has been implemented as a distributed graph. Another contribution is the use of behavior trees instead of state machine for implementing the behavior-based part of the architecture. This late version of the architecture has been tested in robotic competitions (RoboCup or European Robotics League, among others), whose performance is also discussed in this paper.y