| Volume 22 Issue 3 - Publication Date: 1 March 2003 |
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| Neuroethological Concepts and
Their Transfer to Walking Machines |
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| Volker Dürr, André
Krause, Josef Schmitz and Holk Cruse Abteilung Biologische
Kybernetik und Theoretische Biologie, Fakultät für Biologie, Universität
Bielefeld, Postfach 10 01 31, D-33501 Bielefeld, Germany |
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| A systems approach to animal
motor behavior reveals concepts that can be useful for the pragmatic design
of walking machines. This is because the relation of animal behavior to
its underlying nervous control algorithms bears many parallels to the relation
of machine function to electronic control. Here, three major neuroethological
concepts of motor behavior are described in terms of a conceptual framework
based on artificial neural networks (ANN). Central patterns of activity
and postural reflexes are both interpreted as a result of feedback loops,
with the distinction of loops via an internal model from loops via the physical
environment (body, external world). This view allows continuous transitions
between predictive (centrally driven) and reactive (reflex driven) motor
systems. Motor primitives, behavioral modules that are elicited by distinct
commands, are also considered. |
| ANNs capture these three major
concepts in terms of a formal description, in which the interactions and
mutual interdependences of the various output parameters are comprised by
the weight matrix of the net. Based upon behavioral observations of insect
walking, we further demonstrate how a decentralized network of separate
modules, each one described by an ANN, can account for adaptive behavior.
Complex coordination patterns of several manipulators are controlled by
imposing simple interaction rules between limbs, and by exploiting the interaction
of the body with its physical environment. Finally, we discuss the technical
use of leg-like active tactile sensors for obstacle detection, and we show
how specific design of such active sensors may increase efficiency of walking
on rough terrain. Applied to active sensors, an example of parallel, self-organizing
forward models on the basis of extended Kohonen maps is presented to emphasize
the potential of adaptive forward models in motor control. |
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| Multimedia Key |
= Video |
 = Data |
= Code |
= Image |
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Extension |
Type |
Description |
1 |
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Example
One: Behavioral experiment with Crausius morosus. (5.3
MB) |
2 |
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Example
Two: Kinematic stick insect model walking across obstacles. (6.4
MB) |
3 |
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Example
Three: Performance of the WalkNet controller in response to sudden
amputation of the right middle leg (a bird severs the tibia). (3.8
MB) |
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Example
Four: Efficiency evaluation of an active tactile sensor that is
modelled to match a stick insect antenna. (5.2 MB) |
5 |
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Example
Five: Tracking performance of an active tactile sensor driven
by a set of parallel, self-organizing extended Kohonen maps. (4.1
MB) |
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