MCTA: Multi-UAV Collaborative Target Allocation to Monitor Targets with Dynamic Importance

With the development of mechanical manufacturing, wireless communication, and other related technologies, unmanned aerial vehicle (UAV) has become a typical paradigm of IoTs. The emergence of multi-UAV collaboration technology is expected to compensate for the shortcomings of a single UAV, which has become an important research point of IoT applications. The collaboration of multi-UAV is generally driven by scenarios, so we firstly abstract these scenarios into the target allocation problem. Then, we model the constraint of geographic space as an undirected weighted graph. Through a series of rigorous mathematical derivation and theoretical proof, the multi-UAV collaborative target allocation is modeled as a variable scale assignment problem, whose objective is to minimize the battery consumption. Based on that, a heuristic task scheduling algorithm named MCTA is proposed. Through the simulation experiments, the performance of MCTA is effectively evaluated. Compared with three comparison algorithms, MCTA shows many advantages in terms of effectiveness, energy saving, and overall balance.