Capability-Oriented Decision-Making in Multi-UAV Deployment and Task Allocation: A Hierarchical Game-Based Framework
本文提出一种层次博弈框架，将多无人机部署与任务分配联合优化，通过平衡能力指标和两种新算法（TCSA和MDT2A）实现长期服务中的高效决策，仿真验证了方法有效性。
High-level decision-making for multiple uncrewed aerial vehicles (multi-UAV) mission planning is crucial, especially with the rising demand for long-term services in geo-distributed environments. However, the interrelated issues of multi-UAV deployment and task allocation are often addressed separately. This article integrates these two problems and introduces a hierarchical framework for effective decision-making. This is achieved by proposing balanced capability (BC), a customized metric tailored for long-term multi-UAV missions with geographically dispersed targets. By considering the global objective and self-organized coordination, a joint optimization model is established from a game-theoretical perspective. Additionally, a novel tangent and cotangent search algorithm (TCSA) is proposed to steer cooperative players toward the global objective in the upper layer, while in the lower layer, a modified distributed task allocation algorithm (MDT2A) incentivizes each autonomous player to efficiently maximize their individual benefits. Simulations validate the effectiveness of the proposed method, with comparative results highlighting the superiority of the algorithms.