Humanoid robot presentation controlled by multimodal presentation markup language MPML

Nozawa, Yoshinori; Dohi, Hiroshi; Iba, Hitoshi; Ishizuka, Mitsuru

doi:10.1109/roman.2004.1374747

Cited by 13 publications

(6 citation statements)

References 5 publications

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“…Our work can be placed in two research areas: - The area of affective robot tutors, which have already been used in numerous studies (therapy with children with autism spectrum disorders (ASD) (Ismail et al, 2012 ), English classes in primary school (Keren et al, 2012 ), presentations of course contents in primary school (Nozawa et al, 2004 ), etc., and as shown in Saerbeck et al ( 2010 ), improve the efficiency of learning, making students learning more and being more motivated. - The area of affective recommender systems, area which, as described in Salmeron-majadas ( 2014 ), is of great importance in education, due to the strong relationship between emotions and mental processes of cognitive nature.…”

Section: Methodsmentioning

confidence: 99%

ARTIE: An Integrated Environment for the Development of Affective Robot Tutors

Cuadrado¹,

Riesco

López

2016

Front. Comput. Neurosci.

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Over the last decade robotics has attracted a great deal of interest from teachers and researchers as a valuable educational tool from preschool to highschool levels. The implementation of social-support behaviors in robot tutors, in particular in the emotional dimension, can make a significant contribution to learning efficiency. With the aim of contributing to the rising field of affective robot tutors we have developed ARTIE (Affective Robot Tutor Integrated Environment). We offer an architectural pattern which integrates any given educational software for primary school children with a component whose function is to identify the emotional state of the students who are interacting with the software, and with the driver of a robot tutor which provides personalized emotional pedagogical support to the students. In order to support the development of affective robot tutors according to the proposed architecture, we also provide a methodology which incorporates a technique for eliciting pedagogical knowledge from teachers, and a generic development platform. This platform contains a component for identiying emotional states by analysing keyboard and mouse interaction data, and a generic affective pedagogical support component which specifies the affective educational interventions (including facial expressions, body language, tone of voice,…) in terms of BML (a Behavior Model Language for virtual agent specification) files which are translated into actions of a robot tutor. The platform and the methodology are both adapted to primary school students. Finally, we illustrate the use of this platform to build a prototype implementation of the architecture, in which the educational software is instantiated with Scratch and the robot tutor with NAO. We also report on a user experiment we carried out to orient the development of the platform and of the prototype. We conclude from our work that, in the case of primary school students, it is possible to identify, without using intrusive and expensive identification methods, the emotions which most affect the character of educational interventions. Our work also demonstrates the feasibility of a general-purpose architecture of decoupled components, in which a wide range of educational software and robot tutors can be integrated and then used according to different educational criteria.

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Section: Methodsmentioning

confidence: 99%

ARTIE: An Integrated Environment for the Development of Affective Robot Tutors

Cuadrado¹,

Riesco

López

2016

Front. Comput. Neurosci.

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“…This section outlines related work on the high-level language approaches to humanoid simulation [6], [7]. Poser Python [8], [9] is an implementation of the Python interpreter.…”

Section: Related Researchmentioning

confidence: 99%

Humanoid Robot Interactions by Motion Description Language and Dialogue

Shukla¹,

Choi²

2013

IJOEE

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This paper describes the development of a system for facilitating humanoid robots to acquire sequence of movements by motion description and dialogue. The unique feature of our system is that we define a descriptive language and framework that allows the specification of humanoid motions and the representation of motor skills. We subsequently developed and tested a virtual reality simulation system that can execute the motion descriptive language. We then extended the system to allow humanoid robots to acquire motion descriptions through conversing with human. We implemented and tested the proposed system on the NAO humanoid robot. Our implementation includes a dialogue module that continues to update the encoded motion descriptions as the conversation advances and an action module that retrieves the acquired motion descriptions and direct the robot to perform the specified tasks. 

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“…For this reason, small head motions are sometimes introduced in the robot's behavior to indicate liveliness. In (Nozawa et al, 2004), head motions were randomly perturbed to give it visual expression while it talked to compensate for the robot's lack of a mouth. Fig.…”

Section: Applicationsmentioning

confidence: 99%