Plastic Representation of the Reachable Space for a Humanoid Robot

  • Marco Antonelli
  • Beata J. Grzyb
  • Vicente Castelló
  • Angel P. del Pobil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7426)


Reaching a target object requires accurate estimation of the object spatial position and its further transformation into a suitable arm-motor command. In this paper, we propose a framework that provides a robot with a capacity to represent its reachable space in an adaptive way. The location of the target is represented implicitly by both the gaze direction and the angles of arm joints. Two paired neural networks are used to compute the direct and inverse transformations between the arm position and the head position. These networks allow reaching the target either through a ballistic movement or through visually-guided actions. Thanks to the latter skill, the robot can adapt its sensorimotor transformations so as to reflect changes in its body configuration. The proposed framework was implemented on the NAO humanoid robot, and our experimental results provide evidences for its adaptative capabilities.


Humanoid Robot Radial Basis Function Network Hide Unit Plastic Representation Peripersonal Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marco Antonelli
    • 1
  • Beata J. Grzyb
    • 1
  • Vicente Castelló
    • 1
  • Angel P. del Pobil
    • 1
  1. 1.Robotic Intelligence LabUniversitat Jaume ICastellónSpain

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