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Development of Intelligent Behaviors for Social Robots via User-Friendly and Modular Programming Tools

Authors: Enrique Coronado; Fulvio Mastrogiovanni; Gentiane Venture;

Development of Intelligent Behaviors for Social Robots via User-Friendly and Modular Programming Tools

Abstract

The expected adoption of robots able to interact with people in real-world scenarios brings the need to move from easy-to-use to easy-to-develop robot architectures. In this paper, we discuss how a component-based methodology, a block and web-based interface, and a behavior tree approach to the development of robot behaviors can be used together to enable the adoption of the end-user development (EUD) paradigm. The proposed framework (i) mainly uses easy-to-install, cross-platform and modular tools, (ii) is ROS, ZeroMQ and nanomsg compatible, (iii) enables the creation of platform-independent applications, and (iv) can be easily expanded with new sensory devices or robots. In order to evaluate the proposed software framework, an example of a human-robot interaction application using a NAO robot is presented and discussed.

Country
Italy
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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
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