Goal-directed imitation for robots: A bio-inspired approach to action understanding and skill learning

W. Erlhagen, A. Mukovskiy, E. Bicho, G. Panin, C. Kiss, A. Knoll, H. van Schie, H. Bekkering

Research output: Contribution to journalArticlepeer-review

63 Scopus citations


In this paper we present a robot control architecture for learning by imitation which takes inspiration from recent discoveries in action observation/execution experiments with humans and other primates. The architecture implements two basic processing principles: (1) imitation is primarily directed toward reproducing the outcome of an observed action sequence rather than reproducing the exact action means, and (2) the required capacity to understand the motor intention of another agent is based on motor simulation. The control architecture is validated in a robot system imitating in a goal-directed manner a grasping and placing sequence displayed by a human model. During imitation, skill transfer occurs by learning and representing appropriate goal-directed sequences of motor primitives. The robustness of the goal-directed organization of the controller is tested in the presence of incomplete visual information and changes in environmental constraints.

Original languageEnglish
Pages (from-to)353-360
Number of pages8
JournalRobotics and Autonomous Systems
Issue number5
StatePublished - 31 May 2006


  • Action sequence
  • Dynamic field
  • Imitation learning
  • Mirror neurons


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