| dc.description.abstract | With advancements in camera sensor technology, camera sensor networks
are increasingly utilized for border surveillance. UAVs equipped
with downward-facing cameras also serve as effective sensors, and their
features, such as rapid deployment and adjustable field of view, make
them particularly suitable for border surveillance, often termed as
barrier coverage in the literature. This thesis first addresses a barrier
coverage problem using UAVs equipped with downward-facing
cameras. It proposes both deterministic and optimization-based deployment
strategies to ensure barrier coverage. In deterministic deployment,
UAVs are initially aligned to a barrier line to maximize
coverage based on the number of sensors and height constraints. For
optimization-based deployment, a resolution cost of the belt is introduced
to enhance the quality of existing barrier coverage. An optimization
problem is also proposed to achieve barrier coverage with
an overlapping constraint for UAVs placed arbitrarily within the belt.
The approach is further demonstrated to be applicable to borders of
any shape by considering a multi-belt problem. Additionally, a local
fault-tolerance model is proposed to ensure continuous coverage if
some UAVs become faulty. Also, the barrier coverage of a belt with
varying resolution requirements is investigated. For a barrier covered
network with certain regions within the belt that need higher resolutions,
an optimization problem is formulated to determine the final
placement of UAVs ensuring barrier coverage with the requirements.
When handling vision-based sensors for tasks such as intruder detection,
it is essential to account for occlusion caused by objects, as it
can create a false sense of coverage. This thesis addresses the impact
of occluders on barrier coverage networks involving UAVs. The study assesses whether a given UAV network, along with permeable
and impermeable occluders in the belt, achieves barrier coverage. For
permeable occluders, a dual graph approach, one along the length and
one along the width of the belt is introduced to evaluate barrier coverage.
Further, coverage metrics to distinguish any two barrier-covered
networks are proposed. Overall, this thesis provides a comprehensive
study of barrier coverage problems with UAVs, considering both the
presence and absence of occluders. The thesis also tackles the barrier
coverage problem for terrain-like borders using UAVs where achieving
optimal UAV placement is challenging due to factors such as resolution,
overlap constraints, and varying altitudes. We first simplify the
3D problem into an equivalent 2D model and introduce a resolution
cost to assess terrain coverage quality. Additionally, we define the
overlapping length and formulate an optimization problem to secure
barrier coverage.
In the second part of this thesis, the barrier coverage problem with
camera sensor networks is investigated. For a network identified as
barrier-uncovered, an optimization problem is formulated to determine
the optimal positions and orientations of each sensor to ensure
barrier coverage. An attraction force-based motion strategy is then
used to relocate the sensors to the desired positions and orientations.
Similar to UAVs, the impact of occluders on camera sensor networks
is also considered. The limitations of conventional methods are highlighted,
and a coverage model is proposed that introduces a novel sector
division approach, utilizing the interaction between occluders and
sensor regions. Additionally, the existing graph-based method is modified
to assess the barrier coverage of a sensor network in the presence
of occluders. Additionally, deployment strategies for ensuring barrier
coverage when it is initially lacking are discussed. First, a deterministic
approach using a barrier curve derived from a weighted graph is
presented. Finally, an optimization-based deployment strategy, utilizing
the sector division method for barrier coverage constraints, is
proposed to ensure coverage in the presence of occluders. | en_US |
