Robot trajectory prediction and recognition based on a computational mirror neurons model

Link:
Autor/in:
Beteiligte Person:
  • Honkela, Timo
Verlag/Körperschaft:
Springer
Erscheinungsjahr:
2011
Medientyp:
Text
Schlagworte:
  • Robots
  • Demonstrations
  • Dynamic movement
  • Robotics
  • Manipulators
  • Recurrent Neural Network
  • Robot Walking Pattern
  • Mirror Neurons
  • Parametric Bias
  • Robots
  • Demonstrations
  • Dynamic movement
  • Robotics
  • Manipulators
Beschreibung:
  • Mirror neurons are premotor neurons that are considered to play a role in goal-directed actions, action understanding and even social cognition. As one of the promising research areas in psychology, cognitive neuroscience and cognitive physiology, understanding mirror neurons in a social cognition context, whether with neural or computational models, is still an open issue [5]. In this paper, we mainly focus on the action understanding aspect of mirror neurons, which can be regarded as a fundamental function of social cooperation and social cognition. Our proposed initial architecture is to learn a simulation of the walking pattern of a humanoid robot and to predict where the robot is heading on the basis of its previous walking trajectory.
Lizenz:
  • info:eu-repo/semantics/restrictedAccess
Quellsystem:
Forschungsinformationssystem der UHH

Interne Metadaten
Quelldatensatz
oai:www.edit.fis.uni-hamburg.de:publications/10de7bd7-7884-43e3-a829-b795dfef0983