To behave properly in an unknown environment, animals or robots must distinguish external from selfgenerated stimuli on their sensors. The biologically inspired concepts of efference copy and internal model have been successfully applied to a number of robot control problems. Here we present an application of this for our dynamic walking robot RunBot. We use efference copies of the motor commands with a simple forward internal model to predict the expected self-generated acceleration during walking. The difference to the actually measured acceleration is then used to stabilize the walking on terrains with changing slopes through its upper body component controller. As a consequence, the controller drives the upper body component (UBC) to lean forwards/backwards as soon as an error occurs resulting in dynamical stable walking. We have evaluated the performance of the system on four different track configurations. Furthermore we believe that the experimental studies pursued here will sharpen our understanding of how the efference copies influence dynamic locomotion control to the benefit of modern neural control strategies in robots. ; peerReviewed
Using efference copy and a forward internal model for adaptive biped walking
2010-01-01
doi:10.1007/s10514-010-9199-7
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
Using efference copy and a forward internal model for adaptive biped walking
British Library Online Contents | 2010
|Biped walking robot control method and biped walking robot control system
Europäisches Patentamt | 2016
|Using oculo-motor efference to predict a moving target's position
British Library Conference Proceedings | 1998
|Cortical and cerebellar control of sequences of memory-guided saccades: The role of efference copy
British Library Conference Proceedings | 1999
|