  In this paper, we aim to sustain unmanned aerial vehicle (UAV) based missions
for longer periods of times through different techniques. First, we consider
on-the-mission UAV recharging by a low-power laser source (below 1 kilowatt).
In order to achieve the maximal energy gain from the low-power laser source, we
propose an operational compromise, which consists of the UAV resting over
buildings with cleared line-of-sight to the laser source. Second, to provide a
precise energy consumption/harvesting estimation at the UAV, we investigate the
latter's dynamics in a mission environment. Indeed, we study the UAV's battery
dynamics by leveraging the electrical models for motors and battery.
Subsequently, using these models, the path planning problem in a particular
Internet-of-Things based use-case is revisited from the battery perspective.
The objective is to extend the UAV's operation time using both laser-charging
and accurate battery level estimation. Through a graph theory approach, the
problem is solved optimally, and compared to benchmark trajectory approaches.
Numerical results demonstrate the efficiency of this novel battery perspective
for all path planning approaches. In contrast, we found that the energy
perspective is very conservative and does not exploit optimally the available
energy resources. Nevertheless, we propose a simple adjustment method to
correct the energy perspective, by carefully evaluating the energy as a
function of the UAV motion regimes. Finally, the impact of several parameters,
such as turbulence and distance to charging source, is studied.
