We consider the memory system as a key component of any technical cognitive system that can play a central role in bridging the gap between high-level symbolic discrete representations used for reasoning, planning and semantic scene understanding and low-level sensorimotor continuous representations used for control. In this work we described conceptual and technical characteristics such a memory system has to fulfill, together with the underlying data representation. We identify these characteristics based on the experience we gained in developing our ARMAR humanoid robot systems and discuss practical examples that demonstrate what a memory system of a humanoid robot performing tasks in human-centered environments should support, such as multi-modality, introspectability, hetero associativity, predictability or an inherently episodic structure. Based on these characteristics, we extended our robot software framework ArmarX into a unified cognitive architecture that is used in robots of the ARMAR humanoid robot family. Further, we describe, how the development of robot software led us to this novel memory-enabled cognitive architecture and we show how the memory is used by the robots to implement memory-driven behaviors.
翻译:我们认为,记忆系统是任何技术认知系统的一个关键组成部分,可以发挥核心作用,弥合用于推理、规划和语义场景理解的高级象征性离散代表与用于控制的低级别感官和连续代表之间的差距。在这项工作中,我们描述了这种记忆系统的概念和技术特点,以及基本的数据表现。我们根据在开发我们的ARMAR人类机器人系统方面取得的经验,确定了这些特征,并讨论了实际例子,这些实例表明在以人为中心的环境中执行任务的人类机器人的记忆系统应该支持什么,例如多式、易感性、异性、异性关联性、可预测性或固有的分解结构。根据这些特点,我们把我们的机器人软件框架ArmarX扩大到一个统一的认知结构,用于ARMAR人类机器人大家庭的机器人中。此外,我们描述了机器人软件的开发如何引导我们建立这个具有记忆作用的新认知结构,我们展示机器人如何利用记忆来实施记忆驱动的行为。