Human-Guided Trajectory Planning and Control for UAV Swarm in Dense Environment

The dynamic external environment and communication constraints among unmanned aerial vehicles (UAVs) pose challenges to UAV swarm control. Existing methods struggle to ensure the coordination and optimality of swarm movement due to local interactions within the heterogeneous UAV swarm. To address this issue, this article proposes an approach that integrates human intelligence in perception and decision-making into the trajectory planning cost function through a human-machine interaction interface. This makes the planned trajectories more consistent with human intent and environmental constraints. Moreover, individuals within the UAV swarm are divided into different levels, which helps guide the heterogeneous UAV swarm to fly safely in complex environments. High-level UAVs are designated as human-guided UAVs to track the planned trajectory, thus ensuring the smoothness and optimality of swarm movement. Subordinate UAVs operate based on the designed flocking control algorithm, allowing the heterogeneous UAV swarm to navigate through dense environments quickly and safely. Comparative simulation results demonstrate the feasibility, effectiveness, and advantages of the proposed method in improving swarm trajectory smoothness and movement coordination.