A Cognitive Approach to Affordance Learning in Robotic Ecologies

Mauro Dragone

doi:10.1007/978-3-319-19656-5_8

A Cognitive Approach to Affordance Learning in Robotic Ecologies

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

Abstract

The Robotic Ecology vision shares many similarities with the one pursued by the IoT community: The ideal aim on both fronts is that arbitrary combinations of devices should be able to be deployed in unstructured environments, such as those exemplified in a typical household, and there efficiently cooperate to the achievement of complex tasks. While this has the potential to deliver a range of modular and disruptive applications, a pressing and open research question is how to reduce the amount of pre-programming required for their deployment in real world applications. In order to inspire similar advancements within the IoT community, this extended abstract discusses how this goal has been addressed by pioneering the concept of a self-learning robotic ecology within the EU project RUBICON (Robotic UBIquitous Cognitive Network); how such an approach relates to the concept of Affordances at the basis of Gibsons’ theory of ecological psychology; and how it can be used to drive the gradual adaptation of a robotic ecology to changing contexts and evolving requirements.

Original language	English
Title of host publication	Internet of Things. User-Centric IoT
Subtitle of host publication	First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I
Editors	Raffaele Giaffreda, Radu-Laurentiu Vieriu, Edna Pasher, Gabriel Bendersky, Antonio J. Jara, Joel J.P.C. Rodrigues, Eliezer Dekel, Benny Mandler
Publisher	Springer
Pages	54-57
Number of pages	4
ISBN (Electronic)	9783319196565
ISBN (Print)	9783319196558
DOIs	https://doi.org/10.1007/978-3-319-19656-5_8
Publication status	Published - 2015

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Publisher	Springer International Publishing
Volume	150
ISSN (Print)	1867-8211

Keywords

Robotic ecology
Affordances
Cognitive systems

Access to Document

10.1007/978-3-319-19656-5_8

Cite this

Dragone, M. (2015). A Cognitive Approach to Affordance Learning in Robotic Ecologies. In R. Giaffreda, R.-L. Vieriu, E. Pasher, G. Bendersky, A. J. Jara, J. J. P. C. Rodrigues, E. Dekel, & B. Mandler (Eds.), Internet of Things. User-Centric IoT: First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I (pp. 54-57). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 150). Springer. https://doi.org/10.1007/978-3-319-19656-5_8

Dragone, Mauro. / A Cognitive Approach to Affordance Learning in Robotic Ecologies. Internet of Things. User-Centric IoT: First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I. editor / Raffaele Giaffreda ; Radu-Laurentiu Vieriu ; Edna Pasher ; Gabriel Bendersky ; Antonio J. Jara ; Joel J.P.C. Rodrigues ; Eliezer Dekel ; Benny Mandler. Springer, 2015. pp. 54-57 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering).

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abstract = "The Robotic Ecology vision shares many similarities with the one pursued by the IoT community: The ideal aim on both fronts is that arbitrary combinations of devices should be able to be deployed in unstructured environments, such as those exemplified in a typical household, and there efficiently cooperate to the achievement of complex tasks. While this has the potential to deliver a range of modular and disruptive applications, a pressing and open research question is how to reduce the amount of pre-programming required for their deployment in real world applications. In order to inspire similar advancements within the IoT community, this extended abstract discusses how this goal has been addressed by pioneering the concept of a self-learning robotic ecology within the EU project RUBICON (Robotic UBIquitous Cognitive Network); how such an approach relates to the concept of Affordances at the basis of Gibsons{\textquoteright} theory of ecological psychology; and how it can be used to drive the gradual adaptation of a robotic ecology to changing contexts and evolving requirements.",

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Dragone, M 2015, A Cognitive Approach to Affordance Learning in Robotic Ecologies. in R Giaffreda, R-L Vieriu, E Pasher, G Bendersky, AJ Jara, JJPC Rodrigues, E Dekel & B Mandler (eds), Internet of Things. User-Centric IoT: First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 150, Springer, pp. 54-57. https://doi.org/10.1007/978-3-319-19656-5_8

A Cognitive Approach to Affordance Learning in Robotic Ecologies. / Dragone, Mauro.
Internet of Things. User-Centric IoT: First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I. ed. / Raffaele Giaffreda; Radu-Laurentiu Vieriu; Edna Pasher; Gabriel Bendersky; Antonio J. Jara; Joel J.P.C. Rodrigues; Eliezer Dekel; Benny Mandler. Springer, 2015. p. 54-57 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 150).

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

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T1 - A Cognitive Approach to Affordance Learning in Robotic Ecologies

AU - Dragone, Mauro

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Y1 - 2015

N2 - The Robotic Ecology vision shares many similarities with the one pursued by the IoT community: The ideal aim on both fronts is that arbitrary combinations of devices should be able to be deployed in unstructured environments, such as those exemplified in a typical household, and there efficiently cooperate to the achievement of complex tasks. While this has the potential to deliver a range of modular and disruptive applications, a pressing and open research question is how to reduce the amount of pre-programming required for their deployment in real world applications. In order to inspire similar advancements within the IoT community, this extended abstract discusses how this goal has been addressed by pioneering the concept of a self-learning robotic ecology within the EU project RUBICON (Robotic UBIquitous Cognitive Network); how such an approach relates to the concept of Affordances at the basis of Gibsons’ theory of ecological psychology; and how it can be used to drive the gradual adaptation of a robotic ecology to changing contexts and evolving requirements.

AB - The Robotic Ecology vision shares many similarities with the one pursued by the IoT community: The ideal aim on both fronts is that arbitrary combinations of devices should be able to be deployed in unstructured environments, such as those exemplified in a typical household, and there efficiently cooperate to the achievement of complex tasks. While this has the potential to deliver a range of modular and disruptive applications, a pressing and open research question is how to reduce the amount of pre-programming required for their deployment in real world applications. In order to inspire similar advancements within the IoT community, this extended abstract discusses how this goal has been addressed by pioneering the concept of a self-learning robotic ecology within the EU project RUBICON (Robotic UBIquitous Cognitive Network); how such an approach relates to the concept of Affordances at the basis of Gibsons’ theory of ecological psychology; and how it can be used to drive the gradual adaptation of a robotic ecology to changing contexts and evolving requirements.

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M3 - Other chapter contribution

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T3 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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A2 - Giaffreda, Raffaele

A2 - Vieriu, Radu-Laurentiu

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A2 - Jara, Antonio J.

A2 - Rodrigues, Joel J.P.C.

A2 - Dekel, Eliezer

A2 - Mandler, Benny

PB - Springer

ER -

Dragone M. A Cognitive Approach to Affordance Learning in Robotic Ecologies. In Giaffreda R, Vieriu RL, Pasher E, Bendersky G, Jara AJ, Rodrigues JJPC, Dekel E, Mandler B, editors, Internet of Things. User-Centric IoT: First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I. Springer. 2015. p. 54-57. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering). doi: 10.1007/978-3-319-19656-5_8

A Cognitive Approach to Affordance Learning in Robotic Ecologies

Abstract

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Keywords

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