Doktorarbeit,
Design of artificial neural oscillatory circuits for the control of lamprey- and salamander-like locomotion using evolutionary algorithms
Department of Artificial Intelligence, University of Edinburgh, UK, (1998)
Zusammenfassung
This dissertation investigates the evolutionary design
of oscillatory artificial neural networks for the
control of animal-like locomotion. It is inspired by
the neural organisation of locomotor circuitries in
vertebrates, and explores in particular the control of
undulatory swimming and walking. The difficulty with
designing such controllers is to find mechanisms which
can transform commands concerning the direction and the
speed of motion into the multiple rhythmic signals sent
to the multiple actuators typically involved in
animal-like locomotion. In vertebrates, such control
mechanisms are provided by central pattern generators
which are neural circuits capable of producing the
patterns of oscillations necessary for locomotion
without oscillatory input from higher control centres
or from sensory feedback. This thesis explores the
space of possible neural configurations for the control
of undulatory locomotion, and addresses the problem of
how biologically plausible neural controllers can be
automatically generated.
Evolutionary algorithms are used to design
connectionist models of central pattern generators for
the motion of simulated lampreys and salamanders. This
work is inspired by Ekeberg's neuronal and mechanical
simulation of the lamprey Ekeberg 93. The first part
of the thesis consists of developing alternative neural
controllers for a similar mechanical simulation. Using
a genetic algorithm and an incremental approach, a
variety of controllers other than the biological
configuration are successfully developed which can
control swimming with at least the same efficiency. The
same method is then used to generate synaptic weights
for a controller which has the observed biological
connectivity in order to illustrate how the genetic
algorithm could be used for developing neurobiological
models. Biologically plausible controllers are evolved
which better fit physiological observations than
Ekeberg's hand-crafted model. Finally, in collaboration
with Jerome Kodjabachian, swimming controllers are
designed using a developmental encoding scheme, in
which developmental programs are evolved which
determine how neurons divide and get connected to each
other on a two-dimensional substrate.
The second part of this dissertation examines the
control of salamander-like swimming and trotting.
Salamanders swim like lampreys but, on the ground, they
switch to a trotting gait in which the trunk performs a
standing wave with the nodes at the girdles. Little is
known about the locomotion circuitry of the salamander,
but neurobiologists have hypothesised that it is based
on a lamprey-like organisation. A mechanical simulation
of a salamander-like animat is developed, and neural
controllers capable of exhibiting the two types of
gaits are evolved. The controllers are made of two
neural oscillators projecting to the limb motoneurons
and to lamprey-like trunk circuitry. By modulating the
tonic input applied to the networks, the type of gait,
the speed and the direction of motion can be varied. By
developing neural controllers for lamprey- and
salamander-like locomotion, this thesis provides
insights into the biological control of undulatory
swimming and walking, and shows how evolutionary
algorithms can be used for developing neurobiological
models and for generating neural controllers for
locomotion. Such a method could potentially be used for
designing controllers for swimming or walking robots,
for instance.
