Coverage Path Planning for UAVs Photogrammetry with Energy and Resolution Constraints

Unmanned Aerial Vehicles (UAVs) are starting to be used for photogrammetric sensing of large areas in several application domains, such as agriculture, rescuing, and surveillance. In this context, the problem of finding a path that covers the entire area of interest is known as Coverage Path Planning (CPP). Although this problem has been addressed by several authors from a geometrical point of view, other issues such as energy, speed, acceleration, and image resolution are not often taken into account. To fill this gap, this paper first proposes an energy model derived from real measurements, and then uses this model to implement a coverage path planning algorithm for reducing energy consumption, as well as guaranteeing a desired image resolution. In addition, two safety mechanisms are presented: the first, executed off-line, checks whether the energy stored in the battery is sufficient to perform the planned path; the second, performed online, triggers a safe return-to-launch (RTL) operation when the actual available energy is equal to the energy required by the UAV to go back to the starting point.