IFIP International Conference on Artificial Intelligence in Theory and Practice

IFIP AI 2010: Artificial Intelligence in Theory and Practice III pp 79-88

Learning Motor Control by Dancing YMCA

  • Rikke Amilde LÄvlid
Conference paper

DOI: 10.1007/978-3-642-15286-3_8

Volume 331 of the book series IFIP Advances in Information and Communication Technology (IFIPAICT)
Cite this paper as:
LÄvlid R.A. (2010) Learning Motor Control by Dancing YMCA. In: Bramer M. (eds) Artificial Intelligence in Theory and Practice III. IFIP AI 2010. IFIP Advances in Information and Communication Technology, vol 331. Springer, Berlin, Heidelberg

Abstract

To be able to generate desired movements a robot needs to learn which motor commands move the limb from one position to another. We argue that learning by imitation might be an efficient way to acquire such a function, and investigate favorable properties of the movement used during training in order to maximize the control system’s generalization capabilities. Our control system was trained to imitate one particular movement and then tested to see if it can imitate other movements without further training.

Download to read the full conference paper text

Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Rikke Amilde LÄvlid
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway