Conceptual representations of actions for autonomous robots

Antonio Chella, Salvatore Gaglio, Roberto Pirrone, Antonio Chella, Roberto Pirrone, Salvatore Gaglio

Risultato della ricerca: Article

25 Citazioni (Scopus)

Abstract

An autonomous robot involved in long and complex missions should be able to generate, update and process its own plans of action. In this perspective, it is not plausible that the meaning of the representations used by the robot is given from outside the system itself. Rather, the meaning of internal symbols must be firmly anchored to the world through the perceptual abilities and the overall activities of the robot. According to these premises, in this paper we present an approach to action representation that is based on a "conceptual" level of representation, acting as an intermediate level between symbols and data coming from sensors. Symbolic representations are interpreted by mapping them on the conceptual level through a mapping mechanism based on artificial neural networks. Examples of the proposed framework are reported, based on experiments performed on a RWI-B12 autonomous robot. © 2001 Elsevier Science B.V.
Lingua originaleEnglish
pagine (da-a)251-263
Numero di pagine13
RivistaRobotics and Autonomous Systems
Volume34
Stato di pubblicazionePublished - 2001

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Autonomous Robots
Robot
Robots
Artificial Neural Network
Update
Internal
Sensor
Experiment
Neural networks
Meaning
Sensors
Experiments
Framework

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications

Cita questo

Conceptual representations of actions for autonomous robots. / Chella, Antonio; Gaglio, Salvatore; Pirrone, Roberto; Chella, Antonio; Pirrone, Roberto; Gaglio, Salvatore.

In: Robotics and Autonomous Systems, Vol. 34, 2001, pag. 251-263.

Risultato della ricerca: Article

Chella, Antonio ; Gaglio, Salvatore ; Pirrone, Roberto ; Chella, Antonio ; Pirrone, Roberto ; Gaglio, Salvatore. / Conceptual representations of actions for autonomous robots. In: Robotics and Autonomous Systems. 2001 ; Vol. 34. pagg. 251-263.
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