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EMRS DTC >
Research Programme > Transducer
Embedded Processing |
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Transducer Embedded Processing
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3D COMPUTER VISION
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SUMMARY
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 The
trend towards asymmetric operations signifies the need
to operate within a military environment characterised
by complexity and uncertainty. Rich and up-to-date surveillance
data needs to be collected from around and within potentially
intricate (e.g. urban) structure. Such structure is
also potentially of the most uncertain and dangerous
kind for military personnel.
Coverage of such complexity implies
multiplicity of sensors, which also implies cheapness
(and disposability). The difficulties of deployment,
and particularly the dangers of human deployment, implies
the use of intelligent sensors and intelligent delivery
platforms.
The intelligent sensor needs not only
to direct its data gathering activity for a primary
surveillance role, but it must also take measures to
ensure its own survival, to get to the places it needs
to be, to position itself to obtain quality data, to
adapt to events and changing circumstances and even
to take specific actions (e.g. designate for a weapon).
Computer vision is the sine qua non
of machine intelligence. In particular, passive vision,
attempts to do what human beings do so readily - use
the huge quantity of free data that exists most of the
time in most places. While computer vision is very difficult
and remains an infant technology, there have been significant
advances in both 3D generic vision for structure analysis,
and scene interpretation in terms of 3D model-based
processes, which are promising real capabilities in
autonomy. These algorithmic advances are generally such
that they require little beyond current sensor capability
and are capable of profitably using the smallest and
cheapest imaging devices.
The proposed work seeks to demonstrate
proof of principle for the basic functionality required
of autonomous machines in these environments.
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MILITARY BENEFITS
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Intelligent platforms can act as a
force multiplier, providing data or performing actions
that military personnel might otherwise have to carry
out. While such devices will be necessarily much less
capable than human beings, they can add to effectiveness
either by weight of numbers, by going where human beings
cannot or do not wish to go or by playing sacrificial
or dispensable roles. The essential requirements, if
such force multiplication is anticipated, are cheapness
and intelligence.
CRP programmes have already indicated
a significant military interest in the use of unmanned
vehicles and it is understood that further focus is
now being directed at micro-UAVs. Autonomy is the obvious
logical extension to the UAV concept and the inevitable
requirement of the micro-UAV. Additionally, as UAVs
are increasingly used, there is an increasing likelihood
of such machines straying into civil environments and
there is thus a need to provide greater intelligence
simply to reduce the burden on military personnel of
ensuring such events have minimal impact.
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RESEARCH OBJECTIVE
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The research intends to demonstrate
that small-scale sensor platforms both for ground and
air operation, are capable of operating in directed
autonomous mode within complex environments, both containing
natural (e.g. vegetative) entities and human artefact
(e.g. buildings). We aim to show that such platforms
can journey through such environments, surviving, navigating,
mapping and planning, largely on the basis of passive
computer vision.
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RESEARCH OUTLINE
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The overall concept of sensor platforms
that can survive, navigate and plan for action or information
gathering within complex environments, is ambitious
and not all such functionality is achievable within
a programme of this size. Nevertheless, it is believed
that the essential survival and navigation functionality
will be demonstrable in real-time on a real platform,
with sufficient human supervision to ensure that infelicities
of performance have no major operational consequences.
Because the Consortium brings to this
project significant expertise in both generic and model-based
3D vision, it is both feasible and sensible to introduce
a demonstration platform early in the programme. It
is believed that at the end of year 1, a live demonstration
can be given of structure-from-motion processes interpreting
the visual scene on a simple mobile platform and providing
navigation and driving commands to it. This demonstration
platform is envisaged as the development machine for
implementing more powerful vision, navigation, mapping
and path planning algorithms during years 2-3.
Structure-from-motion/stereo processes
only provide a partial description of the world at present.
Being feature-based, it is rich where features are well
distributed, sometimes difficult to interpret where
features are dense (e.g. within a tree), and impoverished
where features are sparse. In the latter case human
beings can fill in data by other means (e.g. shape-from-shading),
which algorithmic processes have yet to imitate. Until
computer vision algorithms advance to deal with some
of these more difficult aspects of scene understanding,
there is some promise of assistance from active processes.
3D extraction through active laser devices is explored
as a sub-theme within the EO theme and it is anticipated
that the passive 3D robotic vision programme will be
able to incorporate such inputs in the 2nd and 3rd years
of the research. It is anticipated, therefore, that
a machine vision concept can be developed, in which
intelligently directed active devices can be used to
resolve ambiguities or fill in the gaps within the 3D
representations from the passive vision processes.
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CO-ORDINATION WITH EXISTING /
PREVIOUS RESEARCH
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This research will develop themes
of 3D computer vision which have been the object of
significant previous internally funded programmes and
which represent the state-of-the-art in machine intelligence.
The programme will attempt to align itself with ongoing
MOD concept developments in the area of UAVs and, in
particular micro-UAVs. While the principal vision process
to be investigated is generic (directed at extracting
structure in an unknown world), it is anticipated that
it may develop so as to bring in model-based vision
processes. This draws on internally funded research
programmes (including for applications in the civil
domain, such as ball and player tracking in sports broadcasting
and tool tracking in surgical navigation) and aligns
to current MOD work in precision guidance.
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