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A Unified Internal Representation of the Outer World for Social Robotics

  • Pablo Bustos
  • Luis J. Manso
  • Juan P. Bandera
  • Adrián Romero-Garcés
  • Luis V. Calderita
  • Rebeca Marfil
  • Antonio Bandera
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 418)

Abstract

Enabling autonomous mobile manipulators to collaborate with people is a challenging research field with a wide range of applications. Collaboration means working with a partner to reach a common goal and it involves performing both, individual and joint actions, with her. Human-robot collaboration requires, at least, two conditions to be efficient: a) a common plan, usually under-defined, for all involved partners; and b) for each partner, the capability to infer the intentions of the other in order to coordinate the common behavior. This is a hard problem for robotics since people can change their minds on their envisaged goal or interrupt a task without delivering legible reasons. Also, collaborative robots should select their actions taking into account human-aware factors such as safety, reliability and comfort. Current robotic cognitive systems are usually limited in this respect as they lack the rich dynamic representations and the flexible human-aware planning capabilities needed to succeed in these collaboration tasks. In this paper, we address this problem by proposing and discussing a deep hybrid representation, DSR, which will be geometrically ordered at several layers of abstraction (deep) and will merge symbolic and geometric information (hybrid). This representation is part of a new agents-based robotics cognitive architecture called CORTEX. The agents that form part of CORTEX are in charge of high-level functionalities, reactive and deliberative, and share this representation among them. They keep it synchronized with the real world through sensor readings, and coherent with the internal domain knowledge by validating each update.

Keywords

Social robotics World internalization Deep representations 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pablo Bustos
    • 1
  • Luis J. Manso
    • 1
  • Juan P. Bandera
    • 2
  • Adrián Romero-Garcés
    • 2
  • Luis V. Calderita
    • 1
    • 2
  • Rebeca Marfil
    • 2
  • Antonio Bandera
    • 2
  1. 1.RoboLab GroupUniversity of ExtremaduraCáceresSpain
  2. 2.Dept. Tecnología ElectrónicaUniversity of MalagaMálagaSpain

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