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行动的认知本质——认知心理学、运动科学与机器人技术之间的功能联系

The cognitive nature of action - functional links between cognitive psychology, movement science, and robotics.

作者信息

Schack Thomas, Ritter Helge

机构信息

Neurocognition and Action Research Group, Bielefeld University, Bielefeld, Germany.

出版信息

Prog Brain Res. 2009;174:231-50. doi: 10.1016/S0079-6123(09)01319-3.

Abstract

This paper examines the cognitive architecture of human action, showing how it is organized over several levels and how it is built up. Basic action concepts (BACs) are identified as major building blocks on a representation level. These BACs are cognitive tools for mastering the functional demands of movement tasks. Results from different lines of research showed that not only the structure formation of mental representations in long-term memory but also chunk formation in working memory are built up on BACs and relate systematically to movement structures. It is concluded that such movement representations might provide the basis for action implementation and action control in skilled voluntary movements in the form of cognitive reference structures. To simulate action implementation we discuss challenges and issues that arise when we try to replicate complex movement abilities in robots. Among the key issues to be addressed is the question how structured representations can arise during skill acquisition and how the underlying processes can be understood sufficiently succinctly to replicate them on robot platforms. Working towards this goal, we translate our findings in studies of motor control in humans into models that can guide the implementation of cognitive robot architectures. Focusing on the issue of manual action control, we illustrate some results in the context of grasping with a five-fingered anthropomorphic robot hand.

摘要

本文研究了人类动作的认知架构,展示了其在多个层次上的组织方式以及构建过程。基本动作概念(BACs)被确定为表征层面的主要构建模块。这些BACs是用于掌握运动任务功能需求的认知工具。不同研究方向的结果表明,不仅长期记忆中心理表征的结构形成,而且工作记忆中的组块形成都是基于BACs构建的,并且与运动结构系统地相关。得出的结论是,这种运动表征可能以认知参考结构的形式为熟练的自主运动中的动作执行和动作控制提供基础。为了模拟动作执行,我们讨论了在试图在机器人中复制复杂运动能力时出现的挑战和问题。需要解决的关键问题之一是,在技能习得过程中结构化表征是如何产生的,以及如何足够简洁地理解其潜在过程以便在机器人平台上进行复制。为了实现这一目标,我们将人类运动控制研究中的发现转化为可指导认知机器人架构实现的模型。聚焦于手动动作控制问题,我们在使用五指拟人机器人手抓握的背景下阐述了一些结果。

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