Optimizing the trajectory of drones: trade-off between distance and energy

Abstract

The use of autonomous unmanned aerial vehicles (UAVs) or drones has emerged to efficiently collect data from mobile sensors when there is no infrastructure available. The drones can form a flying ad-hoc network through which the sensors can send their data to a base station at any time. In this paper, we present a mixed integer linear program to find the drones' optimal trajectories to form and maintain this network through time while minimizing their movements and energy consumption. Furthermore we analyze the trade-off between distance and energy, where increasing the drones' mobility can reduce their energy consumption, and derive a fair trade-off optimal solution to balance the two opposite objectives.

Optimizing FANET deployment for mobile sensor tracking in disaster management scenario

“…Taking the drone's movements into consideration, [7] proposed a MILP to build the network while minimizing the drone's movements and energy consumption. With this model, we can know which drone is in which position and therefore how they move from one time step to the other.…”

“…However, associating the drones with the positions turns the problem much more complex. The MILP proposed in [7] has more variables and constraints than the one proposed in [3] and consequently solving it takes more time. In this paper, we extend the work done in [7] to improve its scalability.…”

“…The MILP proposed in [7] has more variables and constraints than the one proposed in [3] and consequently solving it takes more time. In this paper, we extend the work done in [7] to improve its scalability. We use column generation, as in [3], to solve the problem faster.…”

“…( 3)). Constraints (7) ensure that the flow entering a position p occupied by a drone is the same as the flow that leaves p. Hence the positions p ∈ P are used only to route the flow that leaves the base station. Constraints (8) ensure that the total flow entering each mobile sensor must be 1, and so that each sensor is reached.…”

“…To do so, we present a linear program based on a decomposition model that is solved using column generation. This allows us to generate UAV trajectories to continuously cover the sensors and ensure a connected FANET more effectively than a previous model based on mixed-integer linear programming [7].…”