社会适应性机器人的认知架构

Ana Tanevska, F. Rea, G. Sandini, Lola Cañamero, A. Sciutti
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引用次数: 14

摘要

一个能够意识到我们的需求并不断调整其行为的社交机器人,有可能创造出一种复杂的、个性化的、类似人类的互动,就像我们在日常生活中习惯与同伴进行的那种互动。然而,作为学习和犯错过程的结果,适应性也带来了不确定性,作为人类,我们严重依赖于我们使用的机器,使其始终具有可预测性和一致性。为了进一步探索这一点,我们提出了一种支持适应性的人形机器人iCub的认知架构,并试图验证其功能,并确定它可能带来的潜在好处,相对于更传统的机器人预先编写的交互协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cognitive Architecture for Socially Adaptable Robots
A social robot that's aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. However adaptability, being a result of a process of learning and making errors, brings with itself also uncertainty, and we as humans are heavily relying on the machines we use to always be predictable and consistent. To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and establish the potential benefits it could bring with respect to the more traditional pre-scripted interaction protocols for robots.
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