Decentralised Compliant Control for Hexapod Robots: A Stick Insect Based Walking Model
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Date
2007Author
Rosano-Matchain, Hugo Leonardo
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Abstract
This thesis aims to transfer knowledge from insect biology into a hexapod walking
robot. The similarity of the robot model to the biological target allows the testing of
hypotheses regarding control and behavioural strategies in the insect. Therefore, this
thesis supports biorobotic research by demonstrating that robotic implementations are
improved by using biological strategies and these models can be used to understand
biological systems. Specifically, this thesis addresses two central problems in hexapod
walking control: the single leg control mechanism and its control variables; and the
different roles of the front, middle and hind legs that allow a decentralised architecture
to co-ordinate complex behavioural tasks. To investigate these problems, behavioural
studies on insect curve walking were combined with quantitative simulations.
Behavioural experiments were designed to explore the control of turns of freely
walking stick insects, Carausius morosus, toward a visual target. A program for
insect tracking and kinematic analysis of observed motion was developed. The results
demonstrate that the front legs are responsible for most of the body trajectory.
Nonetheless, to replicate insect walking behaviour it is necessary for all legs to contribute
with specific roles. Additionally, statistics on leg stepping show that middle
and hind legs continuously influence each other. This cannot be explained by previous
models that heavily depend on positive feedback controllers. After careful analysis, it
was found that the hind legs could actively rotate the body while the middle legs move
to the inside of the curve, tangentially to the body axis.
The single leg controller is known to be independent from other legs but still capable
of mechanical synchronisation. To explain this behaviour positive feedback controllers
have been proposed. This mechanism works for the closed kinematic chain
problem, but has complications when implemented in a dynamic model. Furthermore,
neurophysiological data indicate that legs always respond to disturbances as a negative
feedback controller. Additional experimental data presented herein indicates that legs
continuously oppose forces created by other legs. This thesis proposes a model that has
a velocity positive feedback control modulated via a subordination variable in cascade
with a position negative feedback mechanism as the core controller. This allows legs
to oppose external and internal forces without compromising inter-leg collaboration
for walking. The single leg controller is implemented using a distributed artificial neural
network. This network was trained with a wider range of movement to that so far
found in the simulation model. The controller implemented with a plausible biological