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Underwater vehicle obstacle
avoidance and path planning using a multi-beam forward looking
sonar
Petillot,
Y. Ruiz,
I.T. Lane,
D.M.
Dept. of
Comput. & Electr. Eng., Heriot-Watt Univ.,
Edinburgh;
This paper
appears in: Oceanic Engineering, IEEE Journal
of
On page(s):
240-251
Volume: 26,
Apr
2001
ISSN:
0364-9059
References
Cited: 21
CODEN:
IJOEDY
INSPEC Accession
Number: 6941672
Abstract:
This paper describes a new framework for
segmentation of sonar images, tracking of underwater objects
and motion estimation. This framework is applied to the design
of an obstacle avoidance and path planning system for
underwater vehicles based on a multi-beam forward looking
sonar sensor. The real-time data flow (acoustic images) at the
input of the system is first segmented and relevant features
are extracted. We also take advantage of the real-time data
stream to track the obstacles in following frames to obtain
their dynamic characteristics. This allows us to optimize the
preprocessing phases in segmenting only the relevant part of
the images. Once the static (size and shape) as well as
dynamic characteristics (velocity, acceleration,…) of the
obstacles have been computed, we create a representation of
the vehicle's workspace based on these features. This
representation uses constructive solid geometry (CSG) to
create a convex set of obstacles defining the workspace. The
tracking takes also into account obstacles which are no longer
in the field of view of the sonar in the path planning phase.
A well-proven nonlinear search (sequential quadratic
programming) is then employed, where obstacles are expressed
as constraints in the search space. This approach is less
affected by local minima than classical methods using
potential fields. The proposed system is not only capable of
obstacle avoidance but also of path planning in complex
environments which include fast moving obstacles. Results
obtained on real sonar data are shown and discussed. Possible
applications to sonar servoing and real-time motion estimation
are also discussed
Index Terms:
Kalman
filters collision
avoidance covariance
matrices feature
extraction image
segmentation motion
estimation path
planning quadratic
programming remotely operated
vehicles search
problems sonar
imaging sonar
tracking underwater
vehicles
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