This paper presents a new trajectory planning algorithm for 3D autonomous UAV
volume coverage and visual inspection. The algorithm is an extension of a
state-of-the-art Heat Equation Driven Area Coverage (HEDAC) multi-agent area
coverage algorithm for 3D domains. With a given target exploration density
field, the algorithm designs a potential field and directs UAVs to the regions
of higher potential, i.e., higher values of remaining density. Collisions
between the agents and agents with domain boundaries are prevented by
implementing the distance field and correcting the agent's directional vector
when the distance threshold is reached. A unit cube test case is considered to
evaluate this trajectory planning strategy for volume coverage. For visual
inspection applications, the algorithm is supplemented with camera direction
control. A field containing the nearest distance from any point in the domain
to the structure surface is designed. The gradient of this field is calculated
to obtain the camera orientation throughout the trajectory. Three different
test cases of varying complexities are considered to validate the proposed
method for visual inspection. The simplest scenario is a synthetic portal-like
structure inspected using three UAVs. The other two inspection scenarios are
based on realistic structures where UAVs are commonly utilized: a wind turbine
and a bridge. When deployed to a wind turbine inspection, two simulated UAVs
traversing smooth spiral trajectories have successfully explored the entire
turbine structure while cameras are directed to the curved surfaces of the
turbine's blades. In the bridge test case an efficacious visual inspection of a
complex structure is demonstrated by employing a single UAV and five UAVs. The
proposed methodology is successful, flexible and applicable in real-world UAV
inspection tasks.Comment: 14 page