A novel type of application for the exploration of enclosed or otherwise difficult
to access environments requires large quantities of miniaturized sensor
nodes to perform measurements while they traverse the environment in a “go
with the flow” approach. Examples of these are the exploration of underground
cavities and the inspection of industrial pipelines or mixing tanks, all
of which have in common that the environments are difficult to access and do
not allow position determination using e.g. GPS or similar techniques. The
sensor nodes need to be scaled down towards the millimetre range in order to
physically fit through the narrowest of parts in the environments and should
measure distances between each other in order to enable the reconstruction of
their positions relative to each other in offline analysis. Reaching those levels
of miniaturization and enabling reconstruction functionality requires: 1) novel
reconstruction algorithms that can deal with the specific measurement limitations
and imperfections of millimetre-sized nodes, and 2) improved understanding
of the relation between the highly constraint hardware design
space of the sensor nodes and the reconstruction algorithms. To this end, this
work provides a novel and highly robust sensor swarm reconstruction algorithm
and studies the effect of hardware design trade-offs on its performance.
Our findings based on extensive simulations, which push the reconstruction
algorithm to its breaking point, provide important guidelines for the future
development of millimetre-sized sensor nodes.
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