A neural approach for robot navigation based on cognitive map learning

Link:
Autor/in:
Verlag/Körperschaft:
IEEE
Erscheinungsjahr:
2012
Medientyp:
Text
Schlagworte:
  • Self organizing maps
  • Conformal mapping
  • SOM algorithm
  • Neural Networks
  • Self Organizing Maps
  • Algorithms
  • Self organizing maps
  • Conformal mapping
  • SOM algorithm
  • Neural Networks
  • Self Organizing Maps
  • Algorithms
Beschreibung:
  • This paper presents a neural network architecture for a robot learning new navigation behavior by observing a human's movement in a room. While indoor robot navigation is challenging due to the high complexity of real environments and the possible dynamic changes in a room, a human can explore a room easily without any collisions. We therefore propose a neural network that builds up a memory for spatial representations and path planning using a person's movements as observed from a ceiling-mounted camera. Based on the human's motion, the robot learns a map that is used for path planning and motor-action codings. We evaluate our model with a detailed case study and show that the robot navigates effectively.
  • This paper presents a neural network architecture for a robot learning new navigation behavior by observing a human's movement in a room. While indoor robot navigation is challenging due to the high complexity of real environments and the possible dynamic changes in a room, a human can explore a room easily without any collisions. We therefore propose a neural network that builds up a memory for spatial representations and path planning using a person's movements as observed from a ceiling-mounted camera. Based on the human's motion, the robot learns a map that is used for path planning and motor-action codings. We evaluate our model with a detailed case study and show that the robot navigates effectively. © 2012 IEEE.
Lizenz:
  • info:eu-repo/semantics/closedAccess
Quellsystem:
Forschungsinformationssystem der UHH

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oai:www.edit.fis.uni-hamburg.de:publications/224af84d-3cae-4ce0-b597-c5a81faac3a0