DUET: Joint Deployment of Trucks and Drones for Object Monitoring

The limitation on the flight range motivates a hybrid monitoring system, wherein trucks carrying drones drive to pre-planned positions and then free drones for task execution. While the flight range limitation is mitigated, it is challenging to determine the destination of trucks and drones and set airborne cameras. This paper optimizes the joint Deployment of trUcks and dronEs for objecT monitoring (DUET), that is, deploy a set of trucks where each truck carries drones, and each drone is equipped with a varifocal camera such that the overall monitoring utility for target objects is maximized. To tackle the DUET problem, we first model the hybrid system and monitoring utility; then, discretize the solution space of DUET with performance bound. In this way, the problem is transformed into a two-level combinatorial optimization problem satisfying submodularity. To address it, a two-level greedy algorithm with $\frac{{{{(e - 1)}^2}}}{{e(2e - 1)}} \cdot (1 - \varepsilon )$ approximation ratio is proposed to select deployment strategies. After the strategy selection, an optimal method is devised to carefully adjust the strategy for energy saving and communication improvement without loss of monitoring utility. Both simulations and field experiments are conducted to evaluate the proposed framework, which outperforms baseline algorithms on monitoring utility by at least 28.4% and 40%, respectively.