scholarly journals Social signs processing in a cognitive architecture for an humanoid robot

2018 ◽  
Vol 123 ◽  
pp. 63-68 ◽  
Author(s):  
Agnese Augello ◽  
Emanuele Cipolla ◽  
Ignazio Infantino ◽  
Adriano Manfré ◽  
Giovanni Pilato ◽  
...  
Author(s):  
C. Burghart ◽  
R. Mikut ◽  
R. Stiefelhagen ◽  
T. Asfour ◽  
H. Holzapfel ◽  
...  

2008 ◽  
Vol 05 (04) ◽  
pp. 547-586 ◽  
Author(s):  
KAZUHIKO KAWAMURA ◽  
STEPHEN M. GORDON ◽  
PALIS RATANASWASD ◽  
ERDEM ERDEMIR ◽  
JOSEPH F. HALL

Engineers have long employed control systems utilizing models and feedback loops to control real-world systems. Limitations of model-based control led to a generation of intelligent control techniques such as adaptive and fuzzy control. The human brain, on the other hand, is known to process a variety of inputs in parallel, and shift between different levels of cognitive activities while ignoring distractions to focus on the task in hand. This process, known as cognitive control in psychology, is unique to humans and a handful of animals. We are interested in implementing such cognitive control functionalities for our humanoid robot ISAC. This paper outlines the features of multiagent-based cognitive architecture for a humanoid robot and the progress made toward the realization of cognitive control functionalities using attention, working memory and internal rehearsal. Several experiments have been conducted to show that the implementation of an integrated cognitive robot architecture is feasible.


Author(s):  
David Vernon

AbstractThis paper provides an accessible introduction to the cognitive systems paradigm of enaction and shows how it forms a practical framework for robotic systems that can develop cognitive abilities. The principal idea of enaction is that a cognitive system develops it own understanding of the world around it through its interactions with the environment. Thus, enaction entails that the cognitive system operates autonomously and that it generates its own models of how the world works. A discussion of the five key elements of enaction — autonomy, embodiment, emergence, experience, and sense-making — leads to a core set of functional, organizational, and developmental requirements which are then used in the design of a cognitive architecture for the iCub humanoid robot.


2016 ◽  
Vol 85 (1) ◽  
pp. 3-25 ◽  
Author(s):  
Daniel Hernández García ◽  
Concepción A. Monje ◽  
Carlos Balaguer

Author(s):  
Muhammad Faheem ◽  
Urooj Akram ◽  
Adeel Tariq ◽  
Irfan Khan ◽  
Muhammad Zulqarnain ◽  
...  

2016 ◽  
Vol 14 (1) ◽  
pp. 172988141667813
Author(s):  
Daniel Hernandez Garcia ◽  
Concepcion Monje ◽  
Carlos Balaguer

Future trends in robotics call for robots that can work, interact and collaborate with humans. Developing these kind of robots requires the development of intelligent behaviours. As a minimum standard for behaviours to be considered as intelligent, it is required at least to present the ability to learn skills, represent skill’s knowledge and adapt and generate new skills. In this work, a cognitive framework is proposed for learning and adapting models of robot skills knowledge. The proposed framework is meant to allow for an operator to teach and demonstrate the robot the motion of a task skill it must reproduce; to build a knowledge base of the learned skills knowledge allowing for its storage, classification and retrieval; to adapt and generate new models of a skill for compliance with the current task constraints. This framework has been implemented in the humanoid robot HOAP-3 and experimental results show the applicability of the approach.


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