Dubins Path Planning of Heterogeneous UAV Collaborative Data Collection for IoT Network

Ground-to-air communication is a critical technology for establishing an Internet of Things (IoT) network system, especially in emergency situations. We are investigating the trajectory planning problem of a data collection IoT network assisted by an unmanned aerial vehicle (UAV). This article aims to solve the data collection Dubins traveling salesman problem (DCDTSP) for UAVs in a three-dimensional and complex obstacle environment. To optimize the paths for UAVs in data collection from terminals to UAVs, a novel releasing-collecting-recycling (RCR) framework has been established for heterogeneous multi-UAVs. In the UAV release step, we propose a multi-height hierarchical target clustering (MHTC) algorithm to enhance the efficiency of multi-target clustering. In the data collection step, a bundling ant colony system (BACS) is developed to minimize the length of the obstacle avoidance path while still meeting the communication throughput constraint. Meanwhile, the dynamic adaptive window probabilistic roadmap (DAWPRM) algorithm has been enhanced to address the obstacle avoidance distance in BACS. In the UAV recycling step, we propose a time synchronous Dubins recycling strategy to plan the simultaneous arrival trajectory for multiple UAVs with a constrained turning radius. The results of simulation experiments showed that the proposed RCR framework is optimal for finding Pareto solutions for DCDTSP.