The Influence of Behavioral Complexity on Robot Perception

Vouloutsi, Vasiliki; Grechuta, Klaudia; Lallee, Stéphane; Verschure, Paul F. M. J.

doi:10.1007/978-3-319-09435-9_29

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…3) Behaviors: To regulate the aforementioned drives, the allostatic controller is connected to the behaviors module, and each drive is linked to corresponding behaviors which are supposed to bring it back into its homeostatic range whenever needed. The positive influence of such a drive regulation mechanism on the acceptance of the HRI by naive users has been demonstrated in previous papers [82], [83].…”

Section: Reactive Layermentioning

confidence: 61%

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

Moulin-Frier

Fischer

Petit

et al. 2018

IEEE Trans. Cogn. Dev. Syst.

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Abstract-This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in humanrobot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

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Section: Reactive Layermentioning

confidence: 61%

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

Moulin-Frier

Fischer

Petit

et al. 2018

IEEE Trans. Cogn. Dev. Syst.

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“…Since its implementation as part of the DAC architecture, the H5W library has been intensively used as a tool to support other studies. In particular, it is the core implementation of multiple HRI scenarios such as the exploration of the effects of allostatic control on the human perception of the robot [22,23], or several studies about the effect of other's representation in terms of empathy and ToM [21]. In developmental robotics, it has also been used as a way to maintain the working memory of the robot and served as a base for the development of long term autobiographical memory [77][78][79].…”

Section: Discussionmentioning

confidence: 99%

“…At the same time, the architecture provides useful insight into the robots internal state and motivations, which is due to the careful design the knowledge representation. Our implementation of the architecture has already been presented and validated in several previous studies [21][22][23]; In particular we have investigated the impact of how different robot behaviors are perceived by a human observer or partner.…”

Section: Introductionmentioning

confidence: 99%

How? Why? What? Where? When? Who? Grounding Ontology in the Actions of a Situated Social Agent

Lallee

Verschure

2015

Robotics

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Robotic agents are spreading, incarnated as embodied entities, exploring the tangible world and interacting with us, or as virtual agents crawling over the web, parsing and generating data. In both cases, they require: (i) processes to acquire information; (ii) structures to model and store information as usable knowledge; (iii) reasoning systems to interpret the information; and (iv) finally, ways to express their interpretations. The H5W (How, Why, What, Where, When, Who) framework is a conceptualization of the problems faced by any agent situated in a social environment, which has defined several robotic studies. We introduce the H5W framework, through a description of its underlying neuroscience and the psychological considerations it embodies, we then demonstrate a specific implementation of the framework. We will focus on the motivation and implication of the pragmatic decisions we have taken. We report the numerous studies that have relied upon this technical implementation as a proof of its robustness and polyvalence; moreover, we conduct an additional validation of its applicability to the natural language domain by designing an information exchange task as a benchmark.

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“…These drives present a way to self-regulate value in a dynamic and autonomous way (Sanchez-Fibla et al, 2010 ). This has been shown to positively influence the acceptance of the human-robot interaction by naive users (Vouloutsi et al, 2014 ; Lallée and Verschure, 2015 ).…”

Section: Icub-hri Modulesmentioning

confidence: 99%

iCub-HRI: A Software Framework for Complex Human–Robot Interaction Scenarios on the iCub Humanoid Robot

et al. 2018

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Generating complex, human-like behavior in a humanoid robot like the iCub requires the integration of a wide range of open source components and a scalable cognitive architecture. Hence, we present the iCub-HRI library which provides convenience wrappers for components related to perception (object recognition, agent tracking, speech recognition, and touch detection), object manipulation (basic and complex motor actions), and social interaction (speech synthesis and joint attention) exposed as a C++ library with bindings for Java (allowing to use iCub-HRI within Matlab) and Python. In addition to previously integrated components, the library allows for simple extension to new components and rapid prototyping by adapting to changes in interfaces between components. We also provide a set of modules which make use of the library, such as a high-level knowledge acquisition module and an action recognition module. The proposed architecture has been successfully employed for a complex human-robot interaction scenario involving the acquisition of language capabilities, execution of goal-oriented behavior and expression of a verbal narrative of the robot's experience in the world. Accompanying this paper is a tutorial which allows a subset of this interaction to be reproduced. The architecture is aimed at researchers familiarizing themselves with the iCub ecosystem, as well as expert users, and we expect the library to be widely used in the iCub community.

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The Influence of Behavioral Complexity on Robot Perception

Cited by 5 publications

References 22 publications

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

How? Why? What? Where? When? Who? Grounding Ontology in the Actions of a Situated Social Agent

iCub-HRI: A Software Framework for Complex Human–Robot Interaction Scenarios on the iCub Humanoid Robot

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