INFER-Planner: Information Elapse Rate Planner for AoI-Minimal Data Collection by Heterogeneous Multi-UAV

In the application of multi-UAV assisted ground sensing node data collection, the timeliness represented by age of information is one of the most crucial indicators for evaluating the effectiveness of data collection. Given the heterogeneity of UAVs and ground sensing nodes in this scenario, firstly, each UAV needs to collect data from specific types of nodes, secondly, the information urgency of different nodes is described by the information elapse rate. The planning problem encompasses two aspects including data collecting task allocation and UAV trajectory generation. Consequently, a two-stage planning method is proposed. In the first stage, a topological 3D roadmap is established to precisely calculate the cost of flight time, taking into account ground obstacles and other safety threats. In the second stage, the problem is rephrased as the Heterogeneous Asymmetric Colored Traveling Salesman Problem (HAC-TSP) and then solved using an improved genetic algorithm. The numerical results demonstrate the enhancements achieved by this effort.