Learning the dynamics of the external world: Brain inspired learning for robotic applications

David W. Franklin*, Etienne Burdet, Rieko Osu, Udell So, Keng Peng Tee, Theodore E. Milner, Mitsuo Kawato

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Humans have exceptional abilities to learn new skills, manipulate tools and objects, and interact with our environment. In order to be successful at these tasks, our brain has become exceptionally well adapted to learning to deal not only with the complex dynamics of our own limbs but also with novel dynamics in the external world. While learning of these dynamics includes learning the complex time-varying forces at the end of limbs through the updating of internal models, it must also include learning the appropriate mechanical impedance in order to stabilize both the limb and any objects contacted in the environment. This article reviews the field of human learning by examining recent experimental evidence about adaptation to novel unstable dynamics and explores how this knowledge about the brain and neuro-muscular system can expand the learning capabilities of robotics and prosthetics.

Original languageEnglish
Pages (from-to)109-112
Number of pages4
JournalInternational Congress Series
Publication statusPublished - 2006 Jun
Externally publishedYes


  • Adaptation
  • Force control
  • Impedance control
  • Internal model
  • Metabolic cost

ASJC Scopus subject areas

  • Medicine(all)


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